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0.2763

0.1212

0.1484

0.1569

0.0128

0.1756

Note. coefficientsestimating linear connection (association) of the ranges of each factor withFES and standard errors are applied here.

The lengthier chains of observations ofbarter demand have made it possible to assess how the FES has beeninfluenced by effective and barter demand since quarter IV of the year 1998.The fitting quality of the model utilizing linear interactions of the effectiveand barter demands with the actual FES estimates of the enterprises was lowerthan the fitting quality of the previous model but reliably higher than the 5%threshold. The model’s coefficients for the effective demand were positive and (exceptfor the two January surveys) statistically significant. The coefficients forthe barter demand were mostly negative and always statistically insignificant.And again the calculations confirm that the effective demand can be regarded asthe sole factor positively influencing an enterprise’s situation.

Now let us turn to the plans and forecastsof enterprises. In this case we are going to test the models where theformation of the expected changes in the FESs (again, the real, not thereported ones) occur under the influence of the forecasted values of changes indemand. The application of forecasted values, in our opinion, must moreaccurately reflect the enterprises’ own preferences. In this case the harsh market reality in a lessdefinite manner influences the connections under study.

At first we are going to assess the modelwhere only effective and barter demands are included. To achieve good fittingquality of the model with the participation of the expected FES changes, thecurrent FES estimated must be entered6, without utilizing anyinteractions including the participation of this variable. Themodel’s fittingquality turned out to be exceptionally high: the observed significance levelsin the majority of cases were close to 1 (see Table 17). The influence of thebarter demand forecasts was found to be stable, positive and statisticallysignificant during the whole period under analysis. The influence of theeffective demand forecasts was positive until the second quarter of 2001 butbecame significant only in late 1998 - early 1999. Nevertheless the influenceof the effective demand on the FES was twice as high. Beginning with the secondquarter of the past year, Russian industrial enterprises did not mention barteras a means to improve the values of their business activity even in theirforecasts.

Table 17

Characteristics of the influence offorecasted effective and barter demands on the expected changes of theenterprises’ FES

Date	Characteristics of model’s fitting quality			Model’s coefficients
				effective demand		barter demand
	G2	df	Sig		SE		SE
10/98	152.1469	127	0.0636	0.6007	0.0867	0.2799	0.0850
1/99	119.2811	127	0.6745	0.7723	0.1118	0.3262	0.1147
4/99	116.4677	127	0.7382	0.8791	0.0995	0.0879	0.1047
7/99	87.7935	127	0.9968	1.1099	0.1187	0.1401	0.1001
10/99	86.0843	127	0.9979	0.9600	0.1049	0.0739	0.1164
1/00	90.4826	127	0.9940	1.0157	0.1207	0.2216	0.1239
4/00	130.2608	127	0.4034	1.1752	0.1122	0.0998	0.1122
7/00	88.8699	127	0.9959	1.1374	0.1340	0.0075	0.1242
10/00	82.7119	127	0.9992	0.8934	0.1115	0.0973	0.1042
1/01	88.8818	127	0.9959	1.0020	0.1197	0.1041	0.1170
4/01	54.2137	127	1.0000	1.2547	0.1217	-0.0341	0.1154
7/01	92.4163	127	0.9909	0.9664	0.1288	-0.0269	0.1187
10/01	64.1866	127	1.0000	0.9648	0.1466	-0.0085	0.1438

Note. This table presents: G2 -probability ratio; df - degrees of freedom; Sig - observed significancelevel; coefficients estimating the linear connection (association) of theranges of each factor with FES, and standard errors (SE).

Finally, we are going to consider themodels where all the types of the demand function as independent variables. Thefitting quality turns out to be very high (see Table 18). The model’s coefficients are positive andstatistically significant only for the effective demand. The forecasted valuesof other types of demand do not statistically significantly influence theexpected changes in the FES of Russian industrial enterprises. The coefficientsfor non-monetary types of demand were sometimes negative.

Table 18

Characteristics of the influence offorecasted effective,barter and other non-monetary types of demand on the expected changes of theenterprises’FES

Data	Characteristics of model’s fitting quality			Model’scoefficients
				effective demand		barter demand		other non-monetary types of demand
	G2	Df	Sig		SE		SE		SE
4/00	153.2533	396	1.0000	1.2206	0.1367	0.2838	0.1702	-0.0788	0.1912
7/00	107.3261	396	1.0000	1.2025	0.1648	-0.0570	0.2036	0.3144	0.2196
10/00	117.4724	396	1.0000	0.7667	0.1388	0.1697	0.1717	0.2761	0.1920
1/01	115.9058	396	1.0000	0.9010	0.1366	-0.1445	0.1743	0.4545	0.1939
4/01	76.8033	396	1.0000	1.2257	0.1411	0.0885	0.2027	-0.0040 Pages:     | 1 |   ...   | 10 | 11 | 12 | 13 | 14 |   ...   | 39 |    Книги по разным темам