2020
DOI: 10.3390/agriculture10060217
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Analysis of Dairy Product Price Transmission in Hungary: A Nonlinear ARDL Model

Abstract: This paper addresses the assessment of the price transmission of dairy products in Hungary. Monthly prices are used in testing the hypothesis of asymmetric price transmission between farmers and retailers. The magnitude of short- and long-run asymmetric transmission between price levels is measured through a nonlinear autoregressive distributed model (NARDL). The cointegration of variables is validated through bounds test of the NARDL model. The estimated NARDL model proves the existence of long- and short-run… Show more

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Cited by 11 publications
(6 citation statements)
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“…Second, the prerequisite for using ARDL and NARDL model is to test the stationarity of time series data [ 98 ]. The ADF [ 90 ] and PP [ 91 ] tests examine each data series for unit root.…”
Section: Resultsmentioning
confidence: 99%
“…Second, the prerequisite for using ARDL and NARDL model is to test the stationarity of time series data [ 98 ]. The ADF [ 90 ] and PP [ 91 ] tests examine each data series for unit root.…”
Section: Resultsmentioning
confidence: 99%
“…2 The volatility in prices of aquatic products can reflect the supply and demand of the aquatic products market and the functioning of market mechanisms. 3 However, frequent and significant price volatility not only impacts people's consumption but also affects fishery production. Therefore, ensuring reasonable price volatility and maintaining stability in the aquatic products market are crucial factors in achieving sustainable development in China's fisheries industry.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, the NARDL model has recently been used for measuring the price transmission asymmetry in different countries [34][35][36][37]. In this context and to the best of the author's knowledge no work has been done on the onion price transmission asymmetric analysis by using the NARDL approach in Bangladesh.…”
Section: Introductionmentioning
confidence: 99%