The impact of market and policy instability on price transmission between wheat and flour in Ukraine

Brümmer, Bernhard; Cramon‐Taubadel, Stephan von; Zorya, Sergiy

doi:10.1093/erae/jbp021

Cited by 69 publications

(44 citation statements)

References 23 publications

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“…According to our econometric specification, when shocks occur and price spreads exceed the band, in absolute value, prices tend to converge toward the equilibrium point and to equalize. From this perspective, the specification seems coherent with the formulation of the LOP stated by Alfred Marshall 7 .…”

Section: The Economics and Econometrics Of Price Transmission: Our Mesupporting

confidence: 63%

“…The former way does not imply a price transmission, the latter does, and the faster the reaction of the other price, the faster the deviation returns inside the band. 7 Alfred Marshall (1980) argued that the more an area is characterized by free commerce and perfect competition, the more the prices for the same goods will tend to converge on a common level. ൏ ߠ and trade reverses from the import to the export market).…”

Section: The Economics and Econometrics Of Price Transmission: Our Mementioning

confidence: 99%

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Price Transmission in the European Tomatoes and Cauliflowers Sectors

Santeramo

2015

Agribusiness

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Section: The Economics and Econometrics Of Price Transmission: Our Mesupporting

confidence: 63%

Section: The Economics and Econometrics Of Price Transmission: Our Mementioning

confidence: 99%

Price Transmission in the European Tomatoes and Cauliflowers Sectors

Santeramo

2015

Agribusiness

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“…Thus, the way the product prices are transmitted throughout the marketing chain is traditionally a matter of concern (Bor et al, 2014;Guillen and Artés, 2015;Hahn et al, 2016). However, this issue has frequently been addressed within its aspect of the determination of the transmission between farmer-retailer-consumer prices (Ben- Kaabia, et al, 2005;Abbassi et al, 2012;Rezitis, 2012) instead of examining the right price transmission from the feed to the livestock market (Brümmer et al, 2009;De and Zhou, 2015).…”

Section: Literaturementioning

confidence: 99%

The Spillover Effect of Imported Inputs on Broiler Prices in Turkey

Çınar¹,

Keskin²

2018

New Medit

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“…In some settings, however, regime shifts depend on variables that are unobservable or not amenable to measurement. For example, Brümmer, von Cramon-Taubadel, and Zorya (2009) conjecture that price transmission in the Ukrainian wheat/flour chain is affected by policy interventions that are not always announced officially or enforced evenly over time. The behavior of actors in the chain might change due to such interventions (or threats thereof), leading to changes in price transmission.…”

Section: Motivation In the Context Of Price Transmission Analysismentioning

confidence: 99%

Markov‐Switching Estimation of Spatial Maize Price Transmission Processes between Tanzania and Kenya

Ihle¹,

Cramon‐Taubadel²,

Zorya³

2009

American J Agri Economics

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We discuss the Markov-switching vector autoregressive (MS-VAR) class of nonlinear time series models that can be used to analyze recurring discrete structural changes in time series. Hamilton's (1989) seminal Markovswitching (MS) model of the U.S. business cycle triggered considerable interest in the MS approach in economics. Most empirical applications to date have focused on the business cycle and financial markets, but we see potential for MS-VAR models in agricultural economics, for example, in price transmission analysis. In the following, we first provide an overview of the MS-VAR framework. We then present an illustrative application to maize price transmission between Tanzania and Kenya. The article closes with a discussion of strengths, weaknesses, and potential uses of the MS-VAR approach in price transmission analysis. A Brief Overview of MS-VAR ModelsFollowing Krolzig (1997), the basic idea behind the MS-VAR class of models is that the parameters of a VAR process are allowed to depend on an unobserved regime variable s t ∈ {1, . . . , M}, representing M possible states of the world. In its most general form, the MS-VAR is given bywhere y t = (y 1t , . . . , y Kt ) , t = 1, . . . , T is a Kdimensional time series vector, (s t ) and A j (s t ) are matrices of intercepts and autoregressive (AR) parameters of appropriate dimension, and (s t ) is the variance-covariance matrix of a Gaussian zero-mean error process u t . In (1) the terms (s t ), A j (s t ), and (s t ) describe the dependence of the respective parameters on the unobserved regime s t . The intercept in (1), for example, will be regime-dependent as follows:Hence, the nonlinear data generating process in (1) can be described as piecewise linear (i.e., as linear conditional on the regimes).Depending on which parameters in (1) are allowed to be regime-dependent, different subclasses of the MS-VAR result. Krolzig (1997) proposes the terminology MSx(M)-VAR(p) to distinguish between them, where M is the number of regimes, p the order of the VAR, and x indicates which parameters are regime-dependent. Thus, a MSI(M)-VAR(p) refers to a model in which the intercept is regime-dependent, while MSA(M)-VAR(p) and MSH(M)-VAR(p) refer to regime-dependence in the AR terms A j (s t ) and the error covariance (s t ), respectively. These elements can be combined, so that the "full-blown" model in (1) can be considered a MSIAH(M)-VAR(p).A further sub-class of MS-VAR models that is not immediately apparent from (1) is the MSM(M)-VAR(p) in equation (3) y t − (s t ) = p j=1 A j (y t− j − (s t− j )) + u t ,

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The impact of market and policy instability on price transmission between wheat and flour in Ukraine

Cited by 69 publications

References 23 publications

Price Transmission in the European Tomatoes and Cauliflowers Sectors

Price Transmission in the European Tomatoes and Cauliflowers Sectors

The Spillover Effect of Imported Inputs on Broiler Prices in Turkey

Markov‐Switching Estimation of Spatial Maize Price Transmission Processes between Tanzania and Kenya

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