s[v] = preo[v] s[w] = prvo[w] ∀w ∈ vars(prvo) s[Ov] = o s[Ow] = frozen ∀w ∈ vars(prvo) s[Cw] = v ∀w ∈ vars(prvo) We show that all operators o′ that interfere with Fire(o) are not applicable in s. Thus Fire(o) is the only applicable operator in Ts. Second, we show that for all these operators o′ ∈ Ts (except for Fire(o)), Ts already contains a necessary enabling set for o′ in s. Let u 6= Fire(o)...

In this paper, the structural vector autoregression methodology is used to decompose the euro area nominal short-term interest rate into an expected inflation and an ex-ante real interest rate component. The latter may be a useful indicator of the monetary policy stance of the ECB. To this end, a vector autoregression model comprised of the differenced interest rate series and the stationary co...

This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We use an interacted panel vector autoregression model to explore effects shocks change with regional-level FinTech adoption. Results indicate that adoption generally mitigates transmission real GDP, consumer prices, bank loans, housing prices. A subcategorical a...

Cotton is a strategic crop with a critical role in the economy and agriculture. The increasing price of crop inputs is the main challenge for the developing countries, including Iran, so that it is crucial for the economy of the states to recognize the underpinning factors. Accordingly, the present study aimed to identify the relationship between price shocks of cotton production inputs and cot...

With uncertain changes of the economic environment, macroeconomic downturns during recessions and crises can hardly be explained by a Gaussian structural shock. There is evidence that distribution variables skewed heavy tailed. In this paper, we contribute to literature extending vector autoregression (VAR) model account for more realistic assumptions on multivariate variables. We propose gener...

This paper examines the behavior of forecasts made from a co-integrated system as introduced by Granger (1981), Granger and Weiss (1983) and Engle and Granger (1987). It is established that a multi-step forecast will satisfy the co-integrating relation exactly and that this particular linear combination of forecasts will have a finite limiting forecast error variance. A simulation study compare...