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Ioannis Ganoulis

21 August 2012
WORKING PAPER SERIES - No. 1461
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Abstract
In comparison with the large literature on house prices, housing investments have been studied far less. This paper investigates the behaviour of private residential investments for the six largest European economies, namely: Germany, France, Italy, Spain, the Netherlands and the United Kingdom. It employs a common modelling structure based on an error correction approach and country specific models. First, co-integration among the parsimoniously specified set of fundamental variables is detected in all countries. Second, cross-country differences are found in the responsiveness of private residential investments to real prices and to other relevant factors. Germany has the strongest response of private residential investments to house price changes whereas Italy shows the lowest responses. In Spain investments seem to be primarily related to their lagged component and short-term changes in house prices, and show a poor relationship with deviations from long-term fundamentals. In some countries, the lagged component of residential investments seems to point to a high persistency effect.
JEL Code
C2 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables
R30 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→General
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
17 May 2019
OCCASIONAL PAPER SERIES - No. 223
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Abstract
This paper summarises the outcomes of the analysis of the ECB Crypto-Assets Task Force. First, it proposes a characterisation of crypto-assets in the absence of a common definition and as a basis for the consistent analysis of this phenomenon. Second, it analyses recent developments in the crypto-assets market and unfolding links with financial markets and the economy. Finally, it assesses the potential impact of crypto-assets on monetary policy, payments and market infrastructures, and financial stability. The analysis shows that, in the current market, crypto-assets’ risks or potential implications are limited and/or manageable on the basis of the existing regulatory and oversight frameworks. However, this assessment is subject to change and should not prevent the ECB from continuing to monitor crypto-assets, raise awareness and develop preparedness.
JEL Code
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
16 December 2019
WORKING PAPER SERIES - No. 2341
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Abstract
Using a large set of firm-level survey data from the euro area since 2009, we analyse how firms use their information to form expectations on the availability of bank finance. Our results suggest that firms update what otherwise look like adaptive expectations on the basis of the latest information in their information set. As in the previous literature, the hypothesis that expectations fulfil the (orthogonality) conditions of the rational expectations hypothesis is rejected by the data. We find evidence that this is not only due to information imperfections but also to some type of misspecification of the expectations’ model that firms are using. In addition, we find some evidence that companies that have not used bank finance recently tend to do worse at forecasting its availability next period. To test how policy announcements may affect expectations, we concentrate on the possible effects of the ECB policy announcements of summer 2012, which included among other things the announcement of the European Central Bank’s Outright Monetary Transactions Program (OMT). Using a difference-in-differences approach, we find evidence of forward-looking expectations. In particular, shortly after the OMT announcement the forecast of “informed” firms were more upbeat compared to the control group of firms. This moreover was true in both vulnerable and non-vulnerable countries, suggesting that it was the relevance of the information about the future of the banking system that most mattered for expectations at the time, more than the immediate impact of the announced policy measures.
JEL Code
C83 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Survey Methods, Sampling Methods
D22 : Microeconomics→Production and Organizations→Firm Behavior: Empirical Analysis
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
20 July 2020
WORKING PAPER SERIES - No. 2446
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Abstract
This paper provides novel information on the propagation of the pandemic-induced real shock to firms’ financial conditions. It uses firm-level survey data from end February to early April 2020 for a large sample of euro area SMEs and large firms. Firms’ expectations on the availability of credit lines, bank loans and trade credit deteriorated significantly in the first half of March. Firms mostly expected to be affected if they had previously difficulties in securing finance, had higher indebtedness and, hence, less capacity to deal with a liquidity shock. Conditional on these factors, firm size does not seem to matter, except for trade credit, in which case SMEs had more positive conditional expectations. Together with the overall deterioration of expectations, there seems to have also been a reallocation of opportunities to access finance amidst the crisis. Small firms were more likely to have conditional expectations of improvement in their access to finance.
JEL Code
C83 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Survey Methods, Sampling Methods
D22 : Microeconomics→Production and Organizations→Firm Behavior: Empirical Analysis
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
E65 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Studies of Particular Policy Episodes
L25 : Industrial Organization→Firm Objectives, Organization, and Behavior→Firm Performance: Size, Diversification, and Scope