An efficient tax system is a major factor of dynamic economic development. Yet, in its 13–14 years of economic reform, Russia failed to shape a tax system that could efficiently perform both the regulatory and the fiscal function. In those years, it lacked one essential characteristic, stability. In fact, the years of reform were years of experiments, which failed to yield any tangible results. That this was a dead–end effort was made clear in the 2003 Presidential Message to the RF Federal Assembly, which said that the government’s tax policy was just beginning to make the transition from annual to medium-term planning. This document was also the first to raise the issue of establishing a “reasonable tax rate,” although concrete figures were not mentioned and ways of its optimization and control were not described.
Several factors that make tax regulators very necessary are at work in the economy. First, while on the growth path, the economy becomes more sensitive to the fluctuation of taxes than it was in the preceding crisis period. Second, the issue of rental payments becomes more pressing. This calls for both an adequate methodology helping to evaluate the effectiveness of tax policy, and practical guidelines for optimization of the Russian tax system. The purpose of this article is to illustrate the working of the suggested analytical methods.
Introduction to the problem
One of the latest attempts to empirically analyze fiscal policy effectiveness was made in [1]. It presented what seems to us justified assessments of Laffer points, which delineate the area of effective values of the summary fiscal burden. Simultaneously, an attempt was made to test the suggested econometric methodology for stability. The econometric dependencies and quantitative evaluations found were summarized in [2]. Later, the approach described in [1, 2] was used in [3] to make prognostic calculations. However, further research in this area exposed many other, purely substantive problems and technical faults, which occurred in [1–3]. Let us discuss them in more detail.
First, the RF State Committee for Statistics (Goskomstat) additional data on tax arrears make it necessary to factor in, not only the real fiscal payments and, correspondingly, the level of the real fiscal load, but the nominal fiscal load as well. Actually, we refer to the fact that the nominal fiscal load, which is equal to the summary value of its real (actual) load and the fiscal arrears, should figure in economic analysis as a key measure of effectiveness, of the national tax system. The works [1–3] did not take this into account, whereas it is essential to add this element to the methodology of fiscal analysis: its absence creates the danger of arriving at conclusions that are incorrect in principle and of disorienting the entire managerial decision–making system.
Early steps in this direction were made in [4]. It should be noted here that the available tax arrears statistics imply, by its very essence, a revision of some previous assumptions on the concept and the means of evaluating the potential (nominal) tax burden (see, for example, [5, 6]. In fact, there appears an opportunity to consistently integrate this concept into the overall Laffer curve concept as an element on the basis of a single methodology, something that was impossible before.
Second, the use of the value of summary fiscal load in applied calculations proves divorced from the practical needs of the management system, which can manipulate concrete tax rates but cannot directly change the summary tax load. The econometric instruments for evaluating the effect of summary tax load on economic growth and budget revenues developed in [1] were put aside, in a way, since the summary fiscal load index itself is not a directly controlled variable.
A more rigorous analysis of the approaches used in this area led to the conclusion that in a comparison between the aggregated and disaggregated mode of factoring in the tax burden, priority should be given to the former [4]. This has a number of explanations. Disaggregated methodologies usually optimize the rate of just one tax, while the others remain unchanged. In reality, however, several tax rates change simultaneously. This means that the disaggregated approach unjustifiably simplifies realities and is of little use in applied terms. Attempts to optimize several tax rates at the same time are not very productive, since the “tax portfolio” is usually large enough, and factoring in even the basic fiscal instruments when building models produces cumbersome analytical constructs that are not applicable in practice. Moreover, comparing empirical evaluations obtained on the base of detailed recording of tax regulators demonstrates their extremely controversial character. This fact alone proves that the methodologies in this category lack objectivity. Consequently, the task can be formulated as follows: using the methodology of aggregated recording of the tax load, to expand it so as to establish a link with the final stage of fiscal decision making. In our view, dealing with this problem would make it possible to significantly improve the Laffer curve methodology by closing it up at the final stage, thereby rendering it sufficiently complex and complete.
Third, previous econometric dependencies between GDP and such explanatory variables as labor, capital, and tax burden need to be tested and specified. Despite the fact that applied calculations in [1, 2] helped achieve high quality approximation, some t–statistics of econometric dependencies were insignificant, thereby calling into question the justifiability and sense of the overall scheme of analysis.
Running ahead, let us say that although the qualifying calculations for Great Britain, Sweden, and the United States helped to substantially improve the statistical characteristics of regressions (first of all, t–statistics), thereby making macroeconomic evaluations more reliable, they did not produce noticeable changes in Laffer points, genera 1 and 2. Meanwhile, in the case of Russia, such testing resulted in the construction of an entirely different econometric model and a strong shift of original quantitative estimates. Moreover, the new econometric dependency for the Russian economy initiated a somewhat different scheme of test for invariance of Laffer points. This means that the updating and specification of quantitative evaluations of the overall set of fiscal indicators in question is, by itself, a separate and pressing problem.
Fourth, in the elapsed time, the results described in [1, 2] have been given a new interpretation. The role of Laffer points, genera 1 and 2 as leading fiscal macroindicators became clearer; the dialectic of the stimulating (regulatory) and fiscal (budgetary) functions of tax instruments was seen in a new light; and the faults and limitations of the traditional Laffer curve concept became more obvious. Thus, a better reasoned theoretical substantiation of the econometric methodology used to study Laffer effects makes this issue even more pressing.
Identification of econometric dependencies
The methodology for modeling productive fiscal effects is reflected most fully in the concept of the “split” of the influence of taxes into two components [1]. The first is connected with the study of productive curve Y = Y(q) in the “tax burden (q) vs. production volume (Y)” coordinate system. This curve reaches the local maximum at point q*, which is designated as Laffer point, genus I and for which the following conditions are true: dY(q*)/dq = 0; d^{2}Y(q*)/dq^{2} < 0. The second component is connected with the study of fiscal curve T = T(q) in the “tax burden (q) vs. tax payments (T)” coordinate plane. This curve reaches the local maximum at point q**, which was designated as Laffer point, genus 2: dT(q**)/dq = 0; d^{2}T(q**)/dq^{2} < 0.
In terms of economics, Laffer point, genus 1 means the tax burden limit at which the production system does not yet enter the recession mode. Laffer point, genus 2 indicates the size of the tax burden beyond which increasing tax revenues become impossible. Identification of Laffer points, genera 1 and 2 and their comparison with the actual and nominal tax burden make it possible to assess the quantitative effectiveness of a tax system and to identify its optimization trend. This is the main idea behind the use of the expanded Laffer curve concept.
The deep meaning behind the introduction to the study of two Laffer points is that there is always some antagonism between the regulatory and the fiscal function of the tax system: while it helps replenish a country’s budget, an increase of the tax burden decreases the business activity of economic agents and quenches incentives to production expansion. This shows that the principal problem of fiscal policy is finding a compromise between the interests of the producers and those of the budget.
We note that an introduction to the study of two Laffer points was first undertaken in an explicit form in [7]. Laffer himself and almost all his followers used only one point in their fiscal analysis, namely, the point that in our terminology is designated as Laffer point, genus 2. As for Laffer point, genus 1, for a long time it did not figure in economic constructs; as a result, the fact of the opposition of the two functions of the fiscal system was ignored. Although, at first sight, this state of affairs appears odd, a natural enough explanation of the situation follows.
In view of the above, the foundation of the suggested model toolbox is constituted by the “primary” production–institutional function (PIF) Y = Y(L, F, q), where Y is production (national GDP volume); F is capital (volume of fixed capital); L is labor (volume of employment in the economy); and q is actual fiscal load (share of tax revenues T in GDP, q = T/Y). The fiscal curve, that is, the dependency between the volume of collected tax payments and the tax burden, is described by “secondary” function T = qY = qY(L, F, q). It is the production function Y = Y(L, F, q) that is subject to direct econometric evaluation: this is the reason why it acts as the “primary” dependency; the fiscal function T = qY is obtained by multiplying the production function by the value of fiscal load.
The labor and capital indexes factor in the economy’s resource–related and technological potential, while the fiscal load index, q, reflects the institutional background. This approach is, of course, strongly aggregated and does not pretend to offer a full explanation of all phenomena.
In terms of calculations, index q is the key one in this fiscal analysis; at the macrolevel, it is the share of fiscal payments in GDP withdrawn from individuals and legal entities. The fiscal withdrawals include all tax payments to the budget and the contributions to the non–budgetary funds. The payments made by individuals must be factored in because the load of these payments is indirectly shifted to the businessmen acting as employers.
Applied calculations based on official statistics produced the following “national” PIFs: [1]
for the US economy (1986–2000):
(1)
R2= 0.999; FS = 2037.86; DW = 2.05; N = 15;
for the British economy (1978–1994): [2]
(2)
R2= 0.964; FS = 80.58; DW = 1.73; N = 17;
for the Swedish economy (1980–1994):
(3)
R^{2} = 0.998; FS = 1038.50; DW = 3.21; N = 15.
All three dependencies passed the principal statistical tests and can be considered accurate and workable. [3] In view of this, one can assert that our main hypothesis on the existence of production curve Y, which depends on three variables, including fiscal load, is correct. Unlike the results obtained in [1], dependencies (1)–(3) were subjected to a more thorough examination. In this connection, yet another hypothesis on the existence of a parabolic dependency between production volume and tax burden can also be accepted as final, since the evaluation findings (1)–(3) have a general crosscountry character and leave no room for a different opinion.
It is easy to see that the general form of dependencies (1)–(3) is set by PIF Y = γL^{(α + bq)q}F^{(}^{с} + gq)q, where α, b, c and g are parameters evaluated in statistical terms on the basis of retrospective dynamic series. This function makes it possible to calculate Laffer points, genera 1 and 2 by the formulas:
(4)
(5)
Apart from these two principal fiscal indicators, models (1)–(3) provide an opportunity to build a series of supplementary fiscal system efficiency indicators. Specifically, of great importance are fiscal switch points q_{L} and q_{F}, which satisfy stationary conditions ∂Y(qi)/∂L = 0 and ∂Y(q_{F})/∂F = 0. For the United States, Great Britain, and Sweden, which are described by models (1)–(3), these points are calculated by the formulas q_{L} = –α/b and q_{F} = –c/g.
It would, however, be a mistake to overestimate the generality of this dependency. PIF specification may obviously vary from country to country. The calculations made for the economy of Russia point to the need to modify the econometric model which passed the test in the three above–mentioned countries. Specifically, calculation experiments showed that the fixed capital factor in the Russian economy cannot be smoothly integrated into the analytical scheme: all attempts to integrate into the specification of the econometric model the variables of capital, capital investment, and other indicators derived from fixed capital met with failure (with these indicators, t–statistics proved insignificant). As a result, the following econometric dependency was obtained for Russia 1989–2000:
(6)
R^{2} = 0.963; FS = 117.40; DW = 2.08; N = 12.
A specific feature of function (6) is that the GDP produced in the Russian economy depends only on live labor and burden and does not depend on the volume of the means of production. It is easy to see that the general form of PIF for Russia is given by formula Y = exp(c + αLq + bLq^{2}), where α, b, and с are statistically evaluated parameters. The resulting dependency generates the expression:
For Laffer point, genus 1:
q* = –α/2b (7)
for Laffer point, genus 2, the sought–for expression assumes the form:
(8)
As for the switch points, only one such point exists for model (6), when ∂Y(q_{L})/dL = 0: T_{L} = –αlb.
Although the Russian PIF is obviously truncated as compared to the British, Swedish, and US models, the overall scheme of analysis is the same for Russia.
The system of fiscal indicators: an empirical analysis
The econometric dependencies built make it possible to perform an extensive crosscountry analysis. However, since this has already been done in [1], we shall confine ourselves to the two countries that interest us the most, Russia and the United States. We shall use them as an example to try and show as clearly as possible the potential of the methodology of the expanded Laffer curve concept.
Calculations based on PIF (1) for the US economy by formulas (4) and (5) are presented in Table 1.
Table 1. Fiscal indicators of the US economy, %
A study of the relative positions of values q, q* and q** demonstrated that, in the United States, the fiscal gap between Laffer points, genera 1 and 2 is approximately one percentage point (Table 1). This disparity is within the limits of an ordinary statistical error. This means that in the United States, the reaction of the budget is almost equivalent to that of the producer. Consequently, any above–the–limit fiscal load on the producer automatically worsens the budget situation in the country. One can conclude, therefore, that the US fiscal system is extremely sensitive to production dynamics.
This aspect of the issue also has a theoretical interpretation. The impact of a change in the value of relative fiscal load upon the volume of tax receipts dT/dq can be expressed through production effect dY/dq:
dT/dq = Y + q(dY/dq) (9)
Equation (9) makes it clear that even with a negative production effect, when a rise of taxes reduces the volume of production dY/dq < 0, the size of fiscal revenues may increase [4] dT/dq > 0. The fiscal and the production effects become synchronized only on the edges of the corresponding fiscal and production curves. In the “active” fiscal load zone, a sharp divergence between the two examined effects is observed. As has been pointed out, this is the principal contradiction of government fiscal policy. The broader the band of values between the two Laffer points, the broader the area of fiscal load values where a country’s production and fiscal interests clash.
In view of the fact that in the United States, Laffer points tend to coincide, one can state that the two effects above were practically fully harmonized, and the antagonism between the two sides of fiscal policy almost completely disappeared. In other words, the principle in force in the United States is this: whatever is (good) bad for the producer is good (bad) for the country’s budget, too. As a result, the selection of an effective fiscal burden rate is greatly simplified. In fact, the government is no longer obliged to conduct a “double” analysis of the interests of producers and the consolidated budget. The country’s government can base its forecasts on the producers’ reaction alone.
The absence of visible quantitative differences in the United States between fiscal points, genera 1 and 2 throws light on the one-sidedness of the classical concept of Laffer curve, which uses only the genus 2 point. Years of empirical observations have probably made it clear to the American economist Laffer that the US budget fully depends on the activity of the national business, and this postulate became the foundation of his theory. Needless to say, in the general case, this postulate is invalid.
Our analysis of the intertwining of fiscal and technological factors in the US economy enabled us to evaluate two more fiscal limiting factors: q_{F} = 32.8% and q_{L} = 26.2%. Consequently, the meaning of these indicators is as follows: for marginal labor productivity and marginal capital productivity to be simultaneously positive, the actual fiscal load must lie in the interval q_{L} < q < q_{F}. To be more concrete, the following stringent condition must be observed: 26.2% <q< 32.8%. Table 1 shows that, through 15 years, the actual value of fiscal load in the United States was invariably on this interval. This, on the one hand, shows that the US economy is highly balanced and, on the other, points to opportunities for practical application of such fiscal indicators as switch points q_{L} and q_{F}.
The outcomes of calculations on the basis of PIF (6) for the Russian economy by formulas (7) and (8) are presented in Table 2.
Table 2. Fiscal indicators of the Russian economy, %
Year |
Laffer point, genus |
Laffer point, genus |
A factual fiscal |
Tax arrears^{1}, |
Nominal fiscal load^{1}, (q_{N}) |
1989 |
32.94 |
38.24 |
31.58 |
– |
– |
1990 |
32.94 |
38.26 |
35.64 |
– |
– |
1991 |
32.94 |
38.35 |
32.21 |
– |
– |
1992 |
32.94 |
38.53 |
36.03 |
– |
– |
1993 |
32.94 |
38.70 |
29.53 |
– |
– |
1994 |
32.94 |
39.00 |
30.33 |
2.47 |
32.80 |
1995 |
32.94 |
39.05 |
26.27 |
3.69 |
29.96 |
1996 |
32.94 |
39.15 |
30.94 |
5.97 |
36.91 |
1997 |
32.94 |
39.41 |
33.85 |
7.33 |
41.18 |
1998 |
32.94 |
29.56 |
30.32 |
9.61 |
39.93 |
1999 |
32.94 |
39.14 |
32.19 |
8.18 |
40.37 |
2000 |
32.94 |
39.03 |
35.16 |
6.54 |
41.70 |
1 No data for 1989–1993.
Point q** equaled, on average, 38.9%, and its value was invariably much higher than Laffer point, genus 1. The average fiscal gap between them was six percentage points. This value is very high and points to a conflict between the production and the budgetary criteria for fiscal burden optimization. This is probably where lies the deep difference between the Russian and the US economies. Thus, the production interests of business and the government’s budgetary interests in the United States constitute a certain unity of benchmarks in relation to the optimal rate of fiscal burden, whereas in Russia they are in an irreconcilable conflict.
In terms of absolute fiscal burden, the position of Russian producers is complicated. In 1990, 1992, 1997, and 2000, they were forced to give away more than they were prepared to do in principle. Although the situation in the other years can be described as acceptable, the tax climate in Russia was far from comfortable. Let me note that [1] formulates a diametrically opposite conclusion; in view of this, it is very important to specify the actual state of affairs on the basis of more balanced and correct evaluations.
Evaluation of fiscal switch point q_{L }showed that its value for the Russian economy is 63.6%. Should the fiscal burden exceed it, this could destroy natural technological links in the economy, since in that case, marginal labor productivity would become negative. In the context of this analysis, one can assert that the critical value, q_{L} = 63.6%, is the absolute fiscal load limit beyond which the entire national production system begins to disintegrate. This delimiter is, for Russia, “idle” yet, since overcoming it in practice is absolutely out of the question.
Our understanding of the Russian tax system is promoted by the indicator of nominal fiscal load in the Russian economy (q_{N}), calculated as the sum of actual fiscal burden (q) and the taxes owed to the consolidated budget ( q_{Z}): q_{N}= q + q_{Z}. Component (q_{Z}) is calculated as the GDP share of the total the taxes due to the consolidated budget. [5] Data on tax arrears can be found in the official statistics provided by the RF Goskomstat in the “Finances” section; they are supplied by the RF Ministry for Taxes and Duties. The time series of these data begins since 1994: this means that our analysis covers a long enough period, from 1994 to 2001.
The proposed approach appears quite legitimate, since the tax arrears must be repaid or, in the extreme case, go over to the next fiscal year. On the whole, the actual fiscal load (q) shows the share of real withdrawals, and nominal value (q_{N}) indicates the amount of payment demanded by the state. In fact, tax arrears are something in–between tax evasion and common deferment of payment. The results of calculations are presented in the relevant columns of Table 2.
An estimation n of the fiscal pressure coefficient V = q_{N}/q* shows that during 1997–2000, the state overburdened the producers with taxes to the extent of 20% on average. Russian producers were unable to bear such a tax burden, and this contributed to the growth of tax arrears. In this context, it is noteworthy that as compared to nominal tax burden, actual burden exceeded Laffer point, genus 1 fairly infrequently. This means that however much in tax payments the government may demand, the producers will pay just as much as they are prepared to pay; the rest will assume the form of a debt to the government.
The figures in Table 2 also demonstrate that, in 1997–2000, the Russian authorities, who maximized fiscal revenues of the budget, disregarded the interests of the producer when they established a nominal fiscal load rate that exceeded Laffer point, genus 2, by one or two percentage points. Such excesses arose from bad miscalculations that marked government fiscal policy, which confirms yet again the basic thesis: the fiscal climate in Russia during the time of economic reform cannot be described as liberal (this conclusion is at odds with the hasty conclusion in [1] about the fiscal wellbeing of the Russian economy).
It can be stated, therefore, that at present, the onesided orthodox Laffer curve concept, which uses only Laffer points, genus 2, is altogether unsuitable for the Russian economy; it which requires its expanded version, considered above. The value of the gap between the two Laffer points should act as perhaps the principal criterion and indicator of the efficiency of the national fiscal system.
In this context, it is easy to visualize the logic of fiscal regulation, which can be presented in terms of three goals (guiding principles).The first is to eliminate the contradiction between the interests of the producer and those of the budget, proof of which is the almost complete coincidence of Laffer points, genera 1 and 2: q* ≈ q**. The second is to balance the nominal fiscal load on the left–hand arc of Laffer production curve and to prevent it from going beyond Laffer point, genus 1: q_{N} < q* The third is to enforce tax discipline so as to minimize tax arrears, which would bar the producer from using the primitive method of neutralizing the pressure of taxes by evading them: q_{Z} ≈ 0.
This philosophy of fiscal policy development allows wide use of all the fiscal indicators considered in this article. In view of the simplicity of the proposed tools, they can be of very real help when applied prognostic analytical calculations are made.
Invariance of the values of fiscal indicators
To decide conclusively the question of the efficiency of the indicators considered above, first of all, Laffer points, genera 1 and 2, we must find proof of their correctness and objectivity. With this end in view, let us consider the issue of invariance of Laffer points, that is, check calculated values q* and q** for stability, as was done in [2].
Different tests for invariance of fiscal indicators were used for the United States and for Russia. For the former, in the initial model specification (1), the size of labor force indicator (L) was replaced by the wage fund indicator (W), and fixed capital (F) by that of capital investment (I). The final dependency took the form
(10)
R^{2}= 0.999; DW = 1.99.
Calculations showed that the change of the mode of macrofactor recording did not cause a shift of the previously obtained values of Laffer points, genera 1 and 2. To confirm this, let us only say that the maximum disparity between Laffer points, genus 1 in the two scenarios was only 0.38 percentage points, and the minimum one was 0.05 percentage points. In the case of Laffer points, genus 2, the deviation was 0.45 and 0.01 percentage points respectively (a more detailed numeric analysis is found in [4]).
In the case of Russia, this model was tested, not by varying the ways of macrofactor recording, but by changing the specification of the model with the same explanatory variables. The final dependency assumed the form of an ordinary quadratic function:
(11)
R^{2}= 0.946; DW = 1.57.
Since the general form of model (11) is expressed by formula Y = с + αLT + bLT^{2}, where α, b, and с are model parameters, Laffer point, genus 1 is determined by formula (7), and Laffer point, genus 2, from the following relation:
(12)
Testing the values of Laffer points for invariance in the case of the Russian economy showed that the genus 1 point was determined with a very high degree of accuracy, and that for the genus 2 point the maximum shift was two percentage points, from 37 to 39% of GDR This error can be considered quite satisfactory.
We see, therefore, that the invariance tests of Laffer points for the United States and Russian economies indicate that the qualitative conclusions made in this article deserve to be treated with confidence, since any shifts of quantitative evaluations cannot essentially alter the picture we have drawn.
The influence of individual fiscal instruments on economic growth
Since the final outcome of the analysis of production fiscal effects should be a decision on the change of individual tax rates, the task in question should involve a transition from individual fiscal instruments with their rate values to aggregate fiscal load. If this procedure is accomplished, the impact of each tax on economic growth and budget revenues can be directly evaluated.
To deal with this task, we should use a simple scheme: weigh the taxes for “fiscal power” determined by the tax base. The “fiscal power” indicator of a tax will, in this case, be the elasticity of the summary fiscal load in respect of the interest rate of the tax in question. The elasticity index fixes the number of percentage points by which the summary tax burden will change if the tax rate in question changes by one percentage point. To calculate this value, let us determine the share of i–tax payments in GDP: q_{i} = T_{i}/Y, where T_{i} is the volume of i–type fiscal revenues. Knowing the basic tax rates (s_{i}) and their share in the revenues in relation to GDP (q_{i}), the sought–for fiscal burden elasticity parameter for tax i can be determined by the formula
(13)
The results of the calculations for principal fiscal instruments as applied to Russia’s economy are presented in Table 3.
Table 3. Fiscal characteristics of the Russian economy, 2001
Types of fiscal payments |
Share of fiscal revenues in GDP |
Basic tax rates |
Elasticity indicator |
Profits tax |
5.68 |
24.00 |
0.24 |
VAT |
7.07 |
20.00 |
0.35 |
Property tax |
0.99 |
2.00 |
0.50 |
Deductions to nonbudgetary funds (single social tax) |
6.49 |
35.60 |
0.18 |
The calculated elasticity values, E_{i} make it possible to compare the “fiscal power” of the taxes under consideration. In terms of fiscal load, a change of one percentage point in the property tax proves equivalent to either a two percentage point change of the profit tax or to a 1.4 percentage point change of VAT, or to a 2.7 percentage point change of the common social tax rate. The resulting hierarchy of fiscal instruments provides clear reference points for decision–making regarding their manipulation. Moreover, the fiscal burden elasticity vector (E_{i}) provides an opportunity to conduct variant calculations of the influence of each tax on economic growth rates. Based on the meaning of the indicators introduced, we can do this with the help of a simple relation
(14)
An analogous equation is typical of the budget revenue indicator. When the entire range of fiscal instruments need to be factored in, we can use the formula
(15)
Thus, the approach (13)–(15) implies realizing a very simple two–step algorithm of the influence of tax interest rates on economic growth. At the first step, the influence of changes in the tax interest rate on the aggregate fiscal load, and at the second, the influence of changes in the aggregate fiscal load on economic growth is determined. The first–step calculations are supported by formulas (13), (14), and (15), and the second–step calculations, by econometric models in the form of production–institutional dependencies.
Needless to say, the proposed approach is designed for aggregated calculations. Since economic branches and segments react in different ways to changes of taxes, the proposed averaged calculations will produce good results only when large–scale structural economic transformations are absent. However, in any case, this approach can be used in provisional forecasts of the possible impact of changes in the tax climate on economic growth and budget revenues.
References
1. E. V. Balatskii, “Using Production–Institutional Functions to Analyze the Influence of Tax Load on Economic Growth,” Probl. Prognozir. 14 (2) (2003) [Stud. Russ. Econ. Dev. 14 (2) (2003)].
2. E. V. Balatskii, “The Invariance of Laffer Fiscal Points,” Mirovaya Ekon. Mezhdunar. Otnosheniya, No. 6 (2003).
3. A. B. Gusev, Taxes and Economic Growth: Theories and Empirical Estimators (Ekonomika i pravo, Moscow, 2003) [in Russian].
4. A. B. Gusev, Candidate’s Dissertation in Economics (IMEI, Moscow, 2003).
5. E. V. Balatskii, “Reproduction Cycle and Tax Burden,” Ekon. Matem. Metody, No. 1 (2000).
6. R. Kh. Ibragimov, Candidate’s Dissertation in Economics (IMEI, Moscow, 2001).
7. E. V. Balatskii, “Efficiency of State Fiscal Policy,” Probl. Prognozir. 11 (5) (2000) [Stud. Russ. Econ. Dev. 11 (5) (2000)].
8. http://www.un.org/Depts/unsd/gs_natstat.htm/, list of official sites of national statistical services on the UN site (http://www.un.org).
9. http://www.polyconomics.com/, official site of the University of Supply Economics, USA.
10. http://www.bea.gov/, official site of the Bureau of Economic Analysis, USA.
11. http://www.scb.se/, official site of the Swedish Statistical Office.
12. http://www.statistics.gov.uk/, official site of the National Statistics Service, UK.
13. http://www.ifs.org.uk/, official site of the Institute of Fiscal Studies, UK.
14. http://yu www.minfin.ru/, official site of the RF Ministry of Finance.
15. http://www.nalog.ru/, official site of the RF Ministry of Taxes and Duties.
16. Russian Statistical Yearbook: A Data Book (Goskomstat RF, Moscow, 2002) [in Russian].
[1] The initial data used in the calculation can be found on the official web–sites of the national statistical services and are entered on the relevant register on the UN server [8]. When forming the block of data on the US economy, an extensive use was made of resources [9, 10]; for Sweden, [11]; for Great Britain, [12, 13]; and for Russia, [13–16]. The figures in parentheses under the regressive model coefficients are the values of the corresponding t–statistics; N is the number of observations; R^{2} is the determination coefficient; FS is the value of F–statistics; and DW is the Durbin–Watson autocorrelation coefficient.
[2] For the economies of Great Britain and Sweden, the capital factor (F) was recognized as capital investment because these countries’ national statistical systems lack a fixed capital index.
[3] The author would like to thank A.B. Gusev for assistance in the collection of information and the conduct of calculations, as well as Yu. V. Kuznetsov for his valuable criticism.
[4] This conclusion becomes even more convincing if equation (9) is rewritten in terms of elasticity indicators with account of correlation T = qY(q): μ = 1 + ζ, where ζ = (q/Y)(dY/dq) is the tax elasticity of output; and μ = (q/T)(dT/dq) is the tax elasticity of fiscal revenue. It follows that elasticity li can be positive even when elasticity ζ, is negative.
[5] The fiscal arrears indicator comprises the element of overdue debt. Correspondingly, transferring a debt from one period to another may appear illegitimate when calculating the nominal tax burden rate over a certain period. In our view, however, this procedure is illegitimate only in the case of static (spot) analysis, when just one year is considered. If your analysis becomes dynamic, that is, when temporal (dynamic) series are considered, this approach is justified. In this case, the arrears of the current year include part of the previous year’s arrears, while part of the current year’s arrears goes over to the next year. Such continuity in the intertemporal overflow of overdue fiscal arrears implies their constant presence, which justifies the use of our technique of evaluation of fiscal arrears.
Official link to the article:
Balatskii E.V. The Influence of Fiscal Instruments on Economic Growth: An Evaluation// «Studies on Russian Economic Development», Vol. 15. No. 4. 2004. pp. 412–419.