As the table reveals, the coefficient of the rate of growth in the nominal interest rates reversed its sign and lost its statistical significance in contradistinction to the real interest rates, which considerably gathered in significance. However, the hypothesis about the normality of residuals is rejected (both using the total sampling, and with excluded outliers, see Figs. 11 and 12, Annex 2). However, it shall be mentioned that the distribution of weighted residuals is closer to normal than in case of the non-weighted ones, as is evidenced by smaller values of the Jarque-Bera statistics (compare Figs. 8 and 9 to. Figs. 11 and 12 respectively, Annex 2).

In the similar way the correction was carried out under the assumption that the variance of the explained variable (remaining after the correction for conditional heteroskedasticity) is different across regions. For the results of the model evaluation involving extended correction and exclusion of outliers see Annex 2, Table 20. The variance of the model residuals (Fig. 13, Annex 2) was even closer to the normal and this hypothesis is not rejected at the 99 per cent significance level. Therefore, the use of the WLS method allows to get more precise notion about the significance of evaluations.

According to evaluation results, the rate of growth in the nominal interest became statistically significant with negative sign, what is inconsistent with the hypothesis. A more profound analysis of this relationship reveals that the sign reversal was caused by the interdependence between nominal and real interest, what originated multi-collinearity problems. In case the real interest is shifted one lag back (or excluded from the model), it restores the sign of the coefficient of the nominal interest (see Table 21, Annex 2). Therefore, it would be better not to use these indicators with the same lag.

The evaluation results favor the hypothesis about the importance of bank crediting for the generation of payment arrears, described in the framework of Model 2. The significance of the interest may support both Model 2 and Model 1. As it was asserted above, growth in interest may facilitate the spreading of premeditated non-payments due to the attractiveness of alternative investments and increasing uncertainty.

As it was noted in the theoretical section of this paper, enterprises with longest production cycles experience the most urgent need of credit resources. Therefore, the solvency of such enterprises is more dependent on the availability of credit resources. Accordingly, the presence of a relationship between non-payments and the duration of production cycles may indicate that there exist problems related to the financing of current assets (Model 2, “late payments”).

The duration of production cycle is a micro-economic indicator and is not available from Goskomstat as regional averages. The duration of production cycle may be indirectly characterized by such indicators as capital productivity and capital intensity. Apparently, they are not net characteristics of this indicator. However, it may be suggested that the more rapid is the capital turnover in an industry (region), the less capital intensive is the production and the more rapidly investments are recouped, and, probably, the shorter is the production cycle.

For the testing of this hypothesis see Annex 3. According to the evaluation results the hypothesis is not rejected as the regions with more capital intensive production demonstrate higher propensity to generate payment arrears.

Indicators of Profitability

According to the>

It shall be noted that the relationship between (debtor and creditor) indebtedness and profits (losses) may be of a more complex nature. A write-off of overdue debtor indebtedness (on a certain expiration date) may mean a respective increase in a firm’s losses, while write-offs of creditor indebtedness result in a respective increment in its profits. In this case profits and losses become endogenous variables and outstanding liabilities are an exogenous variable. However, the data indicate that this effect probably had no serious impact on the analyzed process (see Table 1).

The relationship between non-payments and losses, profits, the share of loss-making enterprises as based on regional data was demonstrated in the course of our previous research (see: Lugovoi, Semenov, 2000). Therefore, these data are not presented separately, but included into the generalized model alongside with other factors (real exchange rate, price structure). The impact of this indicator (similarly to real exchange rate) on profitability may not be directly reflected by accounting indicators of profitability (loss-making), due to the disagreement between economic and accounting results of economic operations, concealment of true data about the financial standing of enterprises, changes in output volumes. Therefore, these indicators may be used simultaneously (indicators are not collinear).

The price structure was characterized by the “Index of qualitative changes in producer prices” elaborated and computed by Bessonov (2000). The index describes the national (macro-economic) dynamics, reflecting the fact that the rate of growth in prices of end (processing-intensive) products outpaces the rise in prices of raw materials. There may be suggested a similar indicator characterizing the price structure at the regional level, which shall be computed as a ratio between the accumulated price indices of regional producers and the accumulated regional consumer price indices.

In case the prices of goods produced by regional enterprises outpace inflation (as regards consumer goods) it may be either an evidence that these goods are in good demand, what facilitates the rise in price, or that there is no external competitive pressure.

It is apparent that in case an enterprise sells its products at a higher price (than other producers of similar merchandize), it positively affects its financial standing. Hence a relationship with payment arrears. In case successful enterprises generate less non-payments, an increase in this indicator may reflect their decrease.

Evidently, the enterprises and regions whose products are not included in the consumer basket or have no substitutes are not marketable. It is clear that prices of the raw materials sector are less correlated with consumer prices (at least in the current period), while prices of the sector of end products somewhat affect inflation.

This relationship may also be reviewed via costs. Lagging growth in consumer prices indicates lower production (labor) costs. Low inflation rates account for the abating urgency to adjust wages, therefore relative labor costs decline.

The following model is evaluated:

, (__)(3.1)

where

is the rate of increase in the real Ruble exchange rate;

is the outpacing rate of growth in prices of consumer goods produced by enterprises of the i-th region over the period t, accumulated since the price liberalization (January of 1992);

is the share of loss-making enterprises in the i-th region over the period t.

For the results of model evaluation see Table 4. Similarly to the previous case the WLS method and normalizing weights were applied to evaluate the model.

Table 4. Results of the evaluation of model (3.1), WLS, III/1995-IV/2000.eq04_1

The model’s coefficients are statistically significant and are of the expected signs. The variable representing the share of loss-making enterprises was most statistically significant and positively signed. In other words, the regions with higher shares of loss-making enterprises account for larger non-payments, therefore the growth of this indicator may reflect the increment in payment arrears.

The increase in the real Ruble exchange rate (a decrease in the value of the indicator in Rub./$ terms) registered over the preceding period (quarter) entails an increment in payment arrears. The real exchange rate is statistically insignificant in the current period (without lag).

Changes in the regional price structure (between goods produced and consumed (by households) in the region) also affect payment arrears. According to the hypothesis, the rise in producer prices outpacing the growth in consumer prices may reflect some improvement of financial standing of enterprises and in case there exists a “profitability – payment arrears” relationship result in declining indebtedness.

Therefore, the obtained results confirm the presence of loss-making component in the generation of payment arrears (Model 3). Both the increase in the share of loss-making firms and the dynamics of macro-economic indicators affect non-payments providing the evidence that there exists a channel allowing to finance losses at the expense of payment arrears.

Administration of the State Budget

As it was noted above, budgetary failures may present a source of indebtedness accumulation. Many enterprises engaged in the state procurement operate in such a way that they have to produce first and be paid later. At the same time, their suppliers credit them with energy and raw materials. In this situation delays of budgetary payments result in the fact that budget recipients can not settle with their creditors and thus facilitate the further spreading of payment arrears.

This hypothesis has already been tested basing on aggregate time series in the course of our previous research. This paper tests the hypothesis basing on regional data. The following model is evaluated:

(4.1)

where

is the annualized excess of actual federal budgetary expenditures over targets in per cent of targets (see Fig. 6, Annex 1);

For the results of the evaluation of model coefficients see Table 5. Notwithstanding the correction of quarterly and regional variances and the exclusion of outliers the hypothesis about the absence of heteroskedasticity is rejected (White Heteroskedasticity Test, Annex 2, Table 22. In order to take into account the heteroskedasticity of unknown form there were applied the weights mentioned above (taking into account the quarterly and regional heteroskedasticity) and the White Heteroskedasticity-Consistent Standard Errors & Covariance method.

Table 5. Results of the evaluation of model (__4.1), eq01_1, WLS, White, IV/1994-IV/2000.

According to the evaluation results the budgetary variable is of high statistical significance and is of the expected sign. Therefore, the excess of actual budget indicators over targets was negatively correlated with the growth in non-payments.

The annualized budgetary indicators are stipulated by the law on budget. The targets were broken down by quarters only in 1995. Therefore the budgetary variable used in the model was computed basing on annualized dynamics, its value is identical across all quarters of the same year. The monthly data on budget administration are available, and on the assumption that expenditures are linearly planned14, the utilization of expenditure targets may be calculated for each quarter. It allows the model to take into account dummies for different years (otherwise they will be linearly dependent on the budgetary variable).

Equation (4.1) is evaluated by substituting the budgetary variable with the quarter variable and introducing quarterly dummies (). These variables are intended to take into account the seasonal factor, which may emerge both in the course of the break down of the budgetary variable by quarters, and due to a possible seasonal character of the dependent variable itself. No seasonal differences are applied due to the fact that not all analyzed factors may be submitted to this procedure. Besides, the seasonal differences model reduces the sample and requires special evaluation techniques. The following model is evaluated:

, (__)(4.2)

The results of the model evaluation are presented in Table 6.

Table 6. Results of the evaluation of model (4.2),WLS, White, IV/1994-IV/2000.eq01_2

According to the evaluation results (see Tables 5 and 6), expenditures at 1 per cent below target result in the growth in payment arrears by about 0.33 per cent on the average (coefficient c1 in models 4.1 and 4.2 may be reviewed as elasticity, since both the independent and explained variables are fractional).

The test does not provide evidence about the trend of the detected relationship. It is possible that that the relationship between non-payments and the execution of budgetary expenditures may also be bilateral15. While budgetary expenditure failures may result in the accumulation of payment arrears, the increment in non-payments entail, among other things, that budgetary payment arrears increase (budgetary and extra-budgetary payment arrears are a part of the creditor indebtedness), what results in falling budgetary revenues and therefore failures to meet budgetary expenditures targets. Taking into account this fact, we previously used for modeling the a single lag budgetary variable, thus eliminating the possible feedback. It was not crucial for monthly time series and the significance of the budgetary variable persisted. The following model is evaluated with the lagged variable:

(4.3)

Table 7. Results of the evaluation of model (4.3),WLS, White, IV/1994-IV/2000.eq01_1a

According to the evaluation results the budgetary variable is statistically significant in both models, although at a lower level. At the same time, the absolute value of the coefficient decreases. The significance of the budgetary variable means that the processes of accumulation of overdue indebtedness in the real sector demonstrates the same trend as budgetary failures (and vice versa). Therefore, the budgetary variable without lag will be further used on the assumption that it is exogenous to payment arrears taking into account the fact that this relationship may be of the bilateral nature and requires a further study.

The detected relationship favors the third model, i.e. that loss-making enterprises generate payment arrears. Budgetary failures result in the contraction of state procurement, what affects the effectiveness of enterprises belonging to the public sector and those involved in state procurement.

Материалы этого сайта размещены для ознакомления, все права принадлежат их авторам.
Если Вы не согласны с тем, что Ваш материал размещён на этом сайте, пожалуйста, напишите нам, мы в течении 1-2 рабочих дней удалим его.