This paper uses Hungarian micro-CPI data between December 2001 and June 2007 to provide descriptive statistics of store-level pricing practices in Hungary. First we present simple descriptive statistics about the frequency and average size of price changes, and compare it with similar statistics from other countries. Then we decompose the observed variations in the inflation rate to variations in frequencies and sizes. Finally, we estimate the inflation effects of three general VAT-rate changes during our sample period. Copyright © 2009 John Wiley & Sons, Ltd.
Tanulmányunkban egy, a magyar gazdaságra kalibrált általános egyensúlyi modell segítségével megbecsüljük a munkát terhelő adókulcs Laffer-görbéjét. Eredményeink alapján a költségvetési bevételeket középtávon maximalizáló adókulcs 55 százalék, míg a humántőke-felhalmozást is figyelembe vevő, az adócsökkentés hosszabb távú hatásait is megragadó modellváltozat alapján 40 százalék. Szimulációink szerint a válság előtti magas adóterhelés csökkentése középtávon közel 80 százalékban, míg hosszabb távon teljes mértékben önfinanszírozó. További adócsökkentések esetén az önfinanszírozás aránya az alacsonyabb induló adókulccsal összhangban valamelyest ugyan mérséklődik, de továbbra is magas.
The study uses a general equilibrium model calibrated for the Hungarian economy to estimate the Laffer curve of the labour tax rate. According to the results, the tax rate maximising budget revenues in the medium term is 55 per cent, while based on the model version taking into account the accumulation of human capital and capturing the longer-term effects of a tax cut, it is 40 per cent. The simulations showed that the self-financing rate of the reduction of the labour tax rate from its pre-crisis level to the level in 2011 is roughly 80 per cent over the medium term and that it is fully self-financing in the longer run. In the case of additional tax cuts, the self-financing rate diminishes somewhat in line with the lower tax rate at the outset, but remains high.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.