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Table 2 Results of the vector autoregression models for importers and producers

From: Russian meat price transmission and policy interventions in 2014

Estimated parameter, the explanatory variable Product°°°
k = Beef k = Pork k = Poultry
Dependent variable: ∆It in USD
 \(\mu_{k}^{I}\) 0.002 (0.005) 0.003 (0.01) 0.001 (0.01)
 \(\rho_{l = 1,k}^{I}\), lag of ∆It 0.03 (0.11) 0.12 (0.10)  − 0.13(0.11)
 \(\rho_{l = 2,k}^{I}\), lag of ∆It    − 0.05 (0.10)  
 \(\theta_{j = 1,k}^{I}\), ∆PProduct,t−1 × 1/ERt−1 0.16 (0.07) * 0.027 (0.10) 0.28 (0.12) *
 \(\theta_{j = 2,k}^{I}\), ∆PProduct,t−2 × 1/ERt−2   0.46 (0.10) ***  
 \(\varphi_{n = 1, j = 1}^{I}\), Embargo  − 0.001 (0.02)  − 0.014 (0.05)  − 0.04 (0.04)
 \(\varphi_{n = 1, j = 2}^{I}\), Embargo    − 0.006 (0.05)  
 \(\varphi_{n = 2, j = 1}^{I}\), Pork ban 0.012 (0.01) 0.07 (0.05) 0.04 (0.03)
 \(\varphi_{n = 2, j = 2}^{I}\), Pork ban    − 0.05 (0.05)  
 \(\varphi_{n = 3, j = 1}^{I}\), Exchange rate liberalisation  − 0.017 (0.02)  − 0.03 (0.06) 0.005 (0.04)
 \(\varphi_{n = 3, j = 2}^{I}\), Exchange rate liberalisation   0.03 (0.05)  
 Portmanteau test (p value) 1 0.76 1
 ARCH test (p value) 1 1 1
 Normality test (p value)° 0 0 0
 Stability test passed passed passed
 Granger test (p value)°° 0.46 0.46 0
 Number of observations 84 84 84
 Adjusted R-squared 0.04 0.30 0.06
 p value for F-test (model significance)°°° 0.14 (no) 0 (yes) 0.07 (yes)
Dependent variable: ∆Pt in RUB
 \(\mu_{k}^{P}\) 0.003 (0.004)  − 0.001 (0.005)  − 0.001 (0.004)
 \(\rho_{l = 1,k}^{P}\), ∆Pt−1  − 0.14 (0.12) 0.27 (0.1) * 0.02 (0.1)
 \(\rho_{l = 2,k}^{P}\), ∆Pt−2 0.04 (0.12)   
 \(\theta_{j = 1, k}^{P}\), ∆IProduct,t−1 × ERt−1  − 0.001 (0.06) 0.07 (0.05) 0.05 (0.04)
 \(\theta_{j = 2, k}^{P}\), ∆IProduct,t−2 × ERt−2 0.01 (0.05)   
 \(\gamma_{j = 1,k}^{P}\), ∆EProduct,t−1 × ERt−1 0.012 (0.02) 0.007 (0.008) 0.007 (0.02)
 \(\gamma_{j = 2,k}^{P}\), ∆EProduct,t−2 × ERt−2 0.002 (0.02)   
 \(\varphi_{n = 1, j = 1}^{P}\), Embargo 0.05 (0.03).  − 0.082 (0.02) ***  − 0.04 (0.02) *
 \(\varphi_{n = 1, j = 2}^{P}\), Embargo  − 0.07 (0.03) *   
 \(\varphi_{n = 2, j = 1}^{P}\), Pork Ban 0.003 (0.03) 0.04 (0.01) ** 0.04 (0.01) ***
 \(\varphi_{n = 2, j = 2}^{P}\), Pork Ban 0.002 (0.03)   
 \(\varphi_{n = 3, j = 1}^{P}\), Exchange rate liberalisation 0.06 (0.03). 0.037 (0.02) .  − 0.006 (0.01)
 \(\varphi_{n = 3, j = 2}^{P}\), Exchange rate liberalisation  − 0.05 (0.03).   
 Portmanteau test (p value) 1 0.73 1
 ARCH test (p value) 1 1 1
 Normality test (p value)° 0 0 0
 Stability test passed passed passed
 Granger test (p value)°° 0.03 0.26 0.43
 Observations (number) 84 84 84
 Adjusted R-squared 0 0.26 0.12
 p value for F-test (model significance)°°° 0.55 (no) 0 (yes) 0.01 (yes)
  1. Significance codes: ‘***’p ≤ 0.001, ‘**’p ≤ 0.01, ‘*’p ≤ 0.05, ‘.’p ≤ 0.1. Akaike information criterion is used to define the number of lags. Portmanteau test uses 40 lags, according to default setting of Portmanteau test in Stata specification. ARCH test uses 24 lags. ° The rejected normality is considered not problematic if more than 40 observations are employed (see Ghasemi and Zahediasl 2012). °° H0: dependent variable does not Granger-cause explanatory variable. °°°Overall significance in regression analysis; H0: The fit of the intercept-only model and the assessed model are equal