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Tax reform, the informal economy, and bank financing of capital formation

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Abstract

This paper develops a model that relates businesses’ entry into the underground economy to tax rates and the need to access the banking system. The model uses a dynamic approach in which both firms and banks optimize and in which the benefits to a firm of accessing the banking system are endogenous. A firm compares the return to capital with the marginal tax rate on capital income and uses the difference to determine how much of the tax to pay. At the same time, banks use a firm’s capital tax payments, combined with the capital tax rate to obtain an estimate of the firm’s minimum capital value. If the firm pays at least some taxes then it will have access to the banking system, which will allow it to finance investment. If the firm pays no taxes, then it cannot access the banks and cannot invest. We compare the equilibria resulting from tax compliance and tax evasion.

We calibrate the model to a highly stylized version of the Russian economy, and analyze the effect of potential tax changes on the underground economy. We compute a dynamic equilibrium for our model, and note that it tracks the path of certain macroeconomic variables of the Russian economy (GDP, budget and trade balances, price level and interest rate) with some accuracy for the years 2001–2008. We are unable to track the underground economy, as this data is unobservable. We then carry out a series of counterfactual simulations, first asking if non-capital intensive firms have an incentive to evade taxes under existing value added tax rates. We find that they do, and that the incentive would have been greatly reduced if the value added tax rate had been selectively reduced for the non-capital intensive sectors. We then ask what the effect would be if the corporate tax rate were raised on capital intensive sectors. The simulations indicate that the capital intensive sectors would not increase their entry into the underground economy.

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Notes

  1. See, for example, Gordon and Li (2009) and Emran and Stiglitz (2005), discussing stylized examples of developing countries, in the context of theoretical models. See Piggott and Whalley (2001) for a model with an empirical application to Canada, Feltenstein et al. (2010) for a further example.

  2. It is not specified why the bank cares if the firm has not paid taxes. There may be an underlying notion that a firm that operates illegally is less likely to repay a loan.

  3. Thus in our application we do not try to model evasion issues for the VAT, as these tend to be reflected in actions such as the use of false invoices for input credits and export rebates, issues that are beyond the scope of our analysis.

  4. Investment is assumed to be financed entirely through bank loans.

  5. Russia has introduced reforms in the personal and corporate income taxes, as well as changes in the structure and coverage of the VAT. However, the merits of the reforms and their causal effect on the ensuing developments in the economy, such as increased tax revenue, higher growth rates and higher employment, have been questioned by academics (see Gorodnichenko et al. 2009; Ivanova et al. 2005).

  6. The program that derives the intertemporal equilibrium is written in Fortran 95 and is available from the author upon request.

  7. The number simply corresponds to an aggregation of a standard input–output matrix.

  8. We should note that this treatment of the personal income tax is a simplification of the Russian informal sector, in which for many small firms the personal income tax is really a tax upon both labor and capital income. Thus a more elaborate version of this model would divide firms into corporate and non-corporate sectors.

  9. Clearly this is an ad hoc assumption. We wish to capture the notion that the decision whether or not to pay taxes is based on the relationship between the return to investment and the tax rate on capital.

  10. Here α could be a function of the enforcement technology, hence reflecting risk aversion of the sector. We do not claim to be able to estimate α, but take it to be a simulation variable that is useful in allowing us to judge the impact of different propensities to evade taxes upon equilibrium outcomes.

  11. We assume that all firms within a given industry have the same value for α.

  12. In the next section we develop a simple approach that supposes that a firm’s refusal to pay taxes reduces its ability to borrow from the commercial banking system. Thus a firm’s desire to invest will constrain its evasion of tax payments.

  13. Alternatively, it could aim at maximizing the present discounted real value of the intertemporal sum of returns to capital over time, representing the stream of earnings to the owners of the firm.

  14. The firm could also link its payments of capital taxes to its payments of indirect taxes, reducing both simultaneously.

  15. We suppose that if the firm does not pay indirect taxes then it also would not pay capital taxes, as it could not present a balance sheet to the bank that shows profits but no revenues.

  16. This assumption is thus quite different from GL’s (2009), where the government uses balance sheet information it obtains from the bank in order to tax the firm. Here the firm pays taxes independently of its interaction with the bank. The bank then uses those tax payments to help determine how much to lend. An additional difference is that the bank in GL lends passively.

  17. We have not explicitly incorporated bankruptcies and defaults in this model, for the sake of simplicity. However, bankruptcies and corresponding bank contractions can be introduced as in Ball and Feltenstein (2001).

  18. We would claim that the bank does not really care if the firm is in the formal economy. Its credit rationing rule reflects its estimate of the firm’s capital that can be seized, information that is only available from the tax return.

  19. As before, 1 denotes period i and 2 denotes period i+1.

  20. In fact, because of the assumption of 2-period perfect foresight, it is a 22-dimensional problem replicated in each 2-period segment.

  21. This issue was pointed out by an anonymous referee.

  22. Thus, for example, aggregate Sector 1 comprises Sectors 2–8 in the Russian 48×48 input–output matrix.

  23. The Russian economy exhibited fairly steady growth during the period we examine, so one may question whether the comparison of macro aggregates is really appropriate for our calibration, as we do not capture significant inflections in the economy. Nonetheless, we believe that for our stylized purposes these comparisons do offer some justification.

  24. See http://www.oecd.org/document/32/0,3343,en_2649_34445_42162912_1_1_1_1,00.html.

  25. Thus, for example, for 2010 GDP is 4493.2 billion rubles and general government spending is 8742.2 billion rubles, in the most recent “Use of GDP” table.

Abbreviations

P i :

Price vector of consumption goods in period i

x i :

Vector of consumption in period i

C i :

Value of aggregate consumption in period i (including purchases of financial assets)

N i :

Aggregate income in period i (including potential income from the sale of real and financial assets)

t i :

Vector of VAT rates in period i

P Lui :

Price of urban labor in period i

L ui :

Allocation of total labor to urban labor in period i

x Lui :

Demand for urban leisure in period i

P Lri :

Price of rural labor in period i

L ri :

Allocation of total labor to rural labor in period i

x Lri :

Demand for rural leisure in period i

a 2 :

Elasticity of rural/urban migration

P Ki :

Price of capital in period i

K 0 :

Initial holding of capital

P Ai :

Price of land in period i

A 0 :

Initial holding of land

δ :

Rate of depreciation of capital

P Mi :

Price of money in period i. Money in period 1 is the numeraire and hence has a price of 1

x Mi :

Holdings of money in period I

P Bi :

Discount price of a certificate of deposit in period i

B i :

Domesti c rate of inflation in period i

r i ,r Fi :

The domestic and foreign interest rates in period i

x Bi :

Quantity of bank deposits, that is, CD’s in period i

e i :

The exchange rate in terms of units of domestic currency per unit of foreign currency in period i

x BFi :

Quantity of foreign currency held in period i

TR i :

Transfer payments from the government in period i

a,b,c, β :

Estimated constants

d i :

Constants estimated from model simulations

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Acknowledgements

We would like to thank James Alm, James Cox, Florenz Plassmann, and Gohar Sedrakyan for helpful inputs to this paper.

Author information

Authors and Affiliations

  1. Economics Dept., Andrew Young School of Policy Studies, Georgia State University, P.O. Box 3992, Atlanta, GA, 30302-3992, USA

    Andrew Feltenstein

  2. International Monetary Fund, 700 19th St. NW, Washington, DC, 20431, USA

    Maral Shamloo

Authors
  1. Andrew Feltenstein
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  2. Maral Shamloo
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Correspondence to Andrew Feltenstein.

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The views expressed in this paper are those of the authors and do not necessarily reflect the views of the International Monetary Fund.

Appendices

Appendix A: Consumption

Here, and in what follows, we will use x to denote a demand variable and y to denote a supply variable. In order to avoid unreadable subscripts, let 1 refer to period i and 2 refer to period i+1. The consumer’s maximization problem may be viewed as a standard intertemporal optimization, however subject to a number of constraints. If we consider the set of equations below, the objective function is to maximize consumption of goods and leisure over time. The left-hand side of (5a) represents the value of consumption of goods and leisure, as well as of financial assets. The next two equations contain the value of the consumer’s holdings of capital and labor, as well as the principal and interest that he receives from the domestic and foreign financial assets that he held at the end of the previous period. The equation C i =N i then imposes a budget constraint in each period.

Equation (5b) says that the proportion of savings made up of domestic and foreign interest bearing assets depends upon relative domestic and foreign interest rates, deflated by the change in the exchange rate. Equation (5d) is a migration equation that says that the change in the consumer’s relative holdings of urban and rural labor depends on the relative wage rates. Equation (5c) is a standard money demand equation in which the demand for cash balances depends upon the domestic interest rate and the value of consumption.

Formally, the consumer’s problem is then given by (7). The definition of the notation follows.

$$ \max U(x),\quad x=(x_1, x_{Lu1}, x_{Lr1}, x_2, x_{Lu2}, x_{Lr2})$$
(7)

such that:

(5a)
(5b)

where:

(5c)
(5d)

Appendix B: Parameterization

2.1 B.1 Production

  1. 1.

    Production is based upon the Russian input–output matrix given in Input–Output Tables (edition 2006): access to data, where we use the 2000 Russia input–output matrix.Footnote 24 This matrix is 48×48, with a number of rows and columns of 0s, so as to correspond to the dimension of other OECD input–output matrices. We aggregate to 27×27 to avoid blank rows and columns.

  2. 2.

    Shares of capital and labor in sectoral value added functions are taken from the 2006 IO matrix to form sector specific Cobb–Douglas functions.

  3. 3.

    Government production is given by the share of 2008 government production in GDP. The data is taken from Federal State Statistics Service (http://www.gks.ru/wps/wcm/connect/rosstat/rosstatsite.eng/). We take our data from the GDP definition of “general government” in the “Use of GDP” table.Footnote 25

2.2 B.2 Taxes

  1. 1.

    Value added taxes are taken to be a flat 18 percent with the source being LowTax.Net (http://www.lowtax.net/lowtax/html/offon/russia/rustax.html).

  2. 2.

    The corporate income tax rate is taken to be 24 percent. This is taken from LowTax.Net, with 6.5 percent going to the central government and 17.5 percent going to regional governments, which we aggregate.

  3. 3.

    The personal income tax has a uniform rate of 13 percent which we take from WorldwideTax.com (http://www.worldwide-tax.com/russia/russia_tax.asp).

2.3 B.3 Money demand

We use Korhonen and Mehrotra (2007) to obtain parameters for the money demand equation. The cointegration relationship is estimated as (standard errors in parentheses):

$$\begin{array}{rcl}(m - p)t &=& 1.441yt - 3.337Bt - 0.965et + 0.011t + ut\\&& (0.329)\quad \ (2.952)\quad \ \ (0.122)\quad \ \ (0.001)\end{array}$$

2.4 B.4 Exchange rates

Our model treats exchange rates as being a managed float. Hence for calibration purposes we take exchange rates to be the rate on October 20 of each year from 2001 to 2009. This is an essentially arbitrary date, and an alternative would be to calculate an annual average. Although doing so would make a slight difference in the numerical values of the simulation results, our qualitative results would not change.

2.5 B.5 Consumption

  1. 1.

    Initial allocations of capital and labor are taken from Federal State Statistics Service, GDP Tables 5.1, 6.3, 7.6, 7.7. Initial allocations of land are taken from the IO matrix.

  2. 2.

    Urban and rural populations, employment levels, and initial total incomes are taken from Federal State Statistics Service GDP Table 7.7.

  3. 3.

    Consumption shares in consumer demand functions are given by the corresponding shares from the IO matrix. The urban and rural consumers are assumed to have the same utility functions.

2.6 B.6 Financial assets

Initial money supply, debt, and foreign assets are taken from Ministry of Finance of the Russian Federation: Official Site, Financial Sector, Analytical accounts of the Banking Sector (http://www1.minfin.ru/en/macroeconomics/dessimination/national_summary/#FINANCIALSECTOR)

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Feltenstein, A., Shamloo, M. Tax reform, the informal economy, and bank financing of capital formation. Int Tax Public Finance 20, 1–28 (2013). https://doi.org/10.1007/s10797-012-9213-4

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