The cost of deviating from the optimal monetary policy: A panel VAR analysis

Guerello, Chiara

doi:10.1016/j.jfs.2014.10.004

Cited by 6 publications

(2 citation statements)

References 29 publications

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“…Using the PVAR model allows us to treat both Airbnb and traditional accommodation as endogenous variables. Furthermore, using a vector autoregression (VAR) specification eliminates the endogeneity problem as well as the problem of omitted variable bias, that is, the need to include more proxy variables (cf., for instance, Guerello, 2014). By using time- and county-fixed effects, we are able to control for factors which are equal across counties over time, such as national economic factors.…”

Section: Methodsmentioning

confidence: 99%

Exploring the relationship between Airbnb and traditional accommodation for regional variations of tourism markets

et al. 2021

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The relationship between Airbnb-based and traditional accommodation is mainly documented for key tourist destinations with a large tourism sector, while there is almost no evidence on this for other destinations. This article focuses on regional variations in the relationship between Airbnb-based and traditional accommodation across primary and secondary tourist destinations in Norway. Through an exploratory cluster analysis and a panel vector autoregressive (PVAR) model with forecast error decomposition of shocks (unobserved effects), it finds evidence of spillovers from Airbnb-based accommodation to traditional accommodation in secondary destinations. The demand for traditional accommodation is positively affected by Airbnb demand in the long run. Interestingly, a smaller effect is found with the supply-side of regional tourism markets in the Norwegian secondary tourist destinations. The growth of Airbnb may, thus, spur growth in the general tourism sector in such less frequented destinations.

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Section: Methodsmentioning

confidence: 99%

Exploring the relationship between Airbnb and traditional accommodation for regional variations of tourism markets

et al. 2021

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“…Similar conclusions were reached by Bonfim and Soares (2018), who show that, in general, loans granted during periods of very low and stable interest rates show higher default rates once interest rates start to rise. A different view is presented by Guerello (2014), who employs data from a panel of euro area countries and finds that monetary policy does not have an effect on bank credit risk.…”

Section: Earlier Studies On the Bank Lending And Risk-taking Channelsmentioning

confidence: 99%

Are central banks to blame? Monetary policy and bank lending behavior

Michail

Savva

Koursaros

2021

Bulletin of Econ Res

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This paper tests the conjecture that easy money policies of central banks, that is setting low rates for long, are responsible for the excess risk-taking behavior that led to the global financial crisis. If the conjecture holds then policy rate shocks should have persistent effects on bank behavior either through the bank lending or the risk-taking channel. Using data for the period prior to the global financial crisis, and a shock persistence methodology, we find that the policy rate has only limited idiosyncratic effects on bank lending growth and no effect on credit risk.

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Carbon dioxide emissions reduction in China's transport sector: A dynamic VAR (vector autoregression) approach

Lin

2015

Energy

148

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The cost of deviating from the optimal monetary policy: A panel VAR analysis

Cited by 6 publications

References 29 publications

Exploring the relationship between Airbnb and traditional accommodation for regional variations of tourism markets

Exploring the relationship between Airbnb and traditional accommodation for regional variations of tourism markets

Are central banks to blame? Monetary policy and bank lending behavior

Carbon dioxide emissions reduction in China's transport sector: A dynamic VAR (vector autoregression) approach

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