The name is absent



(industrial prices would not adjust after a shock to the system), but a joint zero restriction of
the speed of adjustment vector is rejected (χ2(3) = 9.807, p = 0.02).

The coefficients of determination are similar to those obtain by other studies ranging between
0.29 and 0.57, thus the model explains a relatively high percent of change in the
macroeconomic variables. The Jarque-Bera statistics reject the normality null at 10% for 3
equations. However, non-normality - implies that the test results must be interpreted with
care, although asymptotic results do hold for a wider class of distributions (von Cramon-
Taubadel, 1998).

Table 8. Residual serial autocorrelation LM and LB tests

Lags

LM-Stat

Prob.a

Lags

LM-Stat

Prob.

1

19.18801

0.2590

7

8.600210

0.9290

2

16.41018

0.4247

8

15.34749

0.4994

3

11.53637

0.7752

9

21.08346

0.1753

4

16.56960

0.4140

10

10.37361

0.8464

5

21.45633

0.1616

11.87551

0.7525

6

20.28460

0.2077

12

21.57624

0.1574

Ljung-Box
statistic
(21)

χ2(244) =288.472
(p = 0.03)

a Probabilities from chi-square with 16 df.

Multivariate LM tests for serial autocorrelation do not reject the no-autocorrelation null
hypothesis for up to the 12th order, but the no-autocorrelation in the first 21 observations null
is rejected.

5. Conclusions

In this research, a theoretical model developed by Shagaian et al. (2002) was employed for a
small, open economy. As most post-communist economies, Hungary experienced numerous
monetary shocks during the transition period, many of them due to the less developed
monetary instruments and ad-hoc measures. Empirical evidence is presented that these shocks
quickly found their way into the agricultural sector causing significant though largely

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