Breaks in the UK Household Sector Money Demand Function.
We use non-parametric procedures to identify breaks in the underlying series of UK household sector money demand functions. Money demand functions are estimated using cointegration techniques and by employing both the Simple Sum and Divisia measures of money. P-star models are also estimated for out...
| Published in: | Manchester School (1463-6786) Vol. 82; no. 2; pp. 47 - 69 |
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| Main Authors: | , , |
| Format: | Article |
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Wiley-Blackwell
Dec2014 Supplement
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=100160434&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 100160434 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 14636786 MSE jtl: Manchester School (1463-6786) issn: 14636786 maglogo: Y pubinfo: dt: Dec2014 Supplement vid: 82 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 100160434 10.1111/manc.12043 ppf: 47 ppct: 22 formats: tig: atl: Breaks in the UK Household Sector Money Demand Function. aug: au: Bissoondeeal, Rakesh Karoglou, Michail Mullineux, Andy affil: Aston University Bournemouth University su: Forecasting Money supply Demand for money Inflation forecasting Central banking industry Interest rates sug: subj: Forecasting Money supply Monetary Authorities-Central Bank Demand for money Inflation forecasting Central banking industry Interest rates ab: We use non-parametric procedures to identify breaks in the underlying series of UK household sector money demand functions. Money demand functions are estimated using cointegration techniques and by employing both the Simple Sum and Divisia measures of money. P-star models are also estimated for out-of-sample inflation forecasting. Our findings suggest that the presence of breaks affects both the estimation of cointegrated money demand functions and the inflation forecasts. P-star forecast models based on Divisia measures appear more accurate at longer horizons and the majority of models with fundamentals perform better than a random walk model. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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