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180614 ||| eng |
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|a 9781484330968
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|a Kongsamut, Piyabha
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|a Incorporating Macro-Financial Linkages into Forecasts Using Financial Conditions Indices: The Case of France
|c Piyabha Kongsamut, Christian Mumssen, Anne-Charlotte Paret, Thierry Tressel
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| 260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2017
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| 300 |
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|a 36 pages
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| 651 |
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4 |
|a France
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| 653 |
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|a Credit
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| 653 |
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|a Wealth
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| 653 |
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|a Stock exchanges
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| 653 |
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|a Investment
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| 653 |
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|a Finance
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| 653 |
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|a Return on investment
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| 653 |
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|a Monetary economics
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| 653 |
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|a Saving
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| 653 |
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|a Economic Forecasting
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| 653 |
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|a Monetary Policy, Central Banking, and the Supply of Money and Credit: General
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| 653 |
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|a Economic forecasting
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| 653 |
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|a General Financial Markets: General (includes Measurement and Data)
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| 653 |
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|a Intangible Capital
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| 653 |
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|a National accounts
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| 653 |
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|a Money
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| 653 |
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|a Forecasting
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| 653 |
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|a Financial markets
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| 653 |
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|a Saving and investment
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| 653 |
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|a Consumption; Economics
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| 653 |
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|a Stock markets
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| 653 |
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|a Forecasting and Other Model Applications
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| 653 |
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|a Investments: General
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| 653 |
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|a Consumption
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| 653 |
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|a Macroeconomics
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| 653 |
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|a Macroeconomics: Consumption
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| 653 |
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|a Capacity
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| 653 |
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|a Capital
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| 653 |
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|a Money and Monetary Policy
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| 653 |
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|a Finance: General
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| 653 |
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|a Forecasting and Simulation: Models and Applications
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| 700 |
1 |
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|a Mumssen, Christian
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| 700 |
1 |
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|a Paret, Anne-Charlotte
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| 700 |
1 |
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|a Tressel, Thierry
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b IMF
|a International Monetary Fund
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| 490 |
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|a IMF Working Papers
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| 028 |
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|a 10.5089/9781484330968.001
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| 856 |
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|u https://elibrary.imf.org/view/journals/001/2017/269/001.2017.issue-269-en.xml?cid=45438-com-dsp-marc
|x Verlag
|3 Volltext
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|a 330
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|a How can information on financial conditions be used to better understand macroeconomic developments and improve macroeconomic projections? We investigate this question for France by constructing country-specific financial conditions indices (FCIs) that are tailored to movements in GDP, investment, private consumption and exports respectively. We rely on a VAR approach to estimate the weights of the financial components of each FCI, including equity market returns (which turn out having a relatively strong weight across all FCIs), private sector risk premiums, long-term interest rates, and banks’ credit standards. We find that the tailored FCIs are useful as leading indicators of GDP, investment, and exports, and as a contemporaneous indicator of private consumption. Credit volumes turn out to be lagging indicators of growth. The indices inform us on macro-financial linkages in France and are used to improve the accuracy of quarterly forecasting models and high-frequency “nowcast” models. We show that FCI-augmented models could have significantly improved forecasts during and after the global financial crisis
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