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Record Nr. |
UNINA9910572199403321 |
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Autore |
Laurìa Antonio |
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Titolo |
Small forgotten places in the heart of cities : on the residuality of public spaces in historical contexts : Florence as a case study / / Antonio Laurìa, Luigi Vesella |
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Pubbl/distr/stampa |
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Florence : , : Firenze University Press, , [2021] |
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©2021 |
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Descrizione fisica |
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1 online resource (156 pages) : illustrations |
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Collana |
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People places architecture |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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This book is the result of a research project designed and carried out at the Department of Architecture, University of Florence. This book discusses urban public spaces and, more specifically, run-down, inactive micro-spaces that are barely used due to their location, dimensions, morphology or semantic characteristics. In literature, these spaces are often defined as "residual urban spaces." A large abandoned industrial area on the outskirts of a town or a small interstitial space in a historical centre can be residual. With respect to such a broad subject matter, the book seeks to radically limit the field, concentrating on public residual spaces found in the oldest parts of cities. The book reflects on this theme and introduces a method for reading and assessment of the residuality of public spaces in historical contexts (Residuality Assessment Process) which was tested in the historical centre of Florence. It is the authors' view that residual spaces, above all if designed according to a system logic, can go from being problems to potential activators of urban and social regeneration processes, offering a useful contribution to improve city life. |
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2. |
Record Nr. |
UNINA9910788519403321 |
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Autore |
Kisinbay Turgut |
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Titolo |
Setting the Operational Framework for Producing Inflation Forecasts / / Turgut Kisinbay, Eric Parrado, Rodolfo Maino, Jorge Canales Kriljenko |
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Pubbl/distr/stampa |
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Washington, D.C. : , : International Monetary Fund, , 2006 |
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ISBN |
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1-4623-2256-5 |
1-4527-3400-3 |
1-282-39162-3 |
9786613820051 |
1-4519-8523-1 |
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Descrizione fisica |
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1 online resource (47 p.) |
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Collana |
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Altri autori (Persone) |
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ParradoEric |
MainoRodolfo |
Canales KriljenkoJorge |
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Soggetti |
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Inflation (Finance) - Forecasting |
Monetary policy |
Banks and banking, Central |
Banks and Banking |
Inflation |
Money and Monetary Policy |
Forecasting |
Banks |
Depository Institutions |
Micro Finance Institutions |
Mortgages |
Forecasting and Other Model Applications |
Price Level |
Deflation |
Monetary Policy |
Interest Rates: Determination, Term Structure, and Effects |
Banking |
Economic Forecasting |
Macroeconomics |
Monetary economics |
Economic forecasting |
Inflation targeting |
Central bank policy rate |
Banks and banking |
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Prices |
Interest rates |
New Zealand |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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""Contents""; ""I. INTRODUCTION""; ""II. FORECAST DESIGN AND ORGANIZATION""; ""III. ELEMENTS OF THE FORECAST""; ""IV. MISCELLANEOUS TOPICS""; ""References"" |
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Sommario/riassunto |
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How should a central bank organize itself to produce the best possible inflation forecast? This paper discusses elements for building a comprehensive platform for an inflation forecasting framework. It describes the exercise of forecasting inflation as a production process, which induces a strict discipline concerning data management, information gathering, the use of a suitable statistical apparatus, and the exercise of sound communication strategies to reinforce reputation and credibility. It becomes critical how a central bank organizes itself to produce relevant macroeconomic forecasts, with special consideration to product design, the essential requirements needed in the forecasting process, and key related organizational issues. In addition, the paper proposes to factor into the process the authorities' policy responses to previous inflation forecasts in order to be consistent with the spirit of the inflation targeting framework. |
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