{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":1,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":43,"n_cols":5,"rows_kept":43,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[32,2,32,3],[33,2,33,3],[37,2,37,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA9910786480703321"]
[null,null,"Autore",null,"Comelli Fabio"]
[null,null,"Titolo",null,"Emerging Market Sovereign Bond Spreads : : Estimation and Back-testing / / Fabio Comelli"]
[null,null,"Pubbl/distr/stampa",null,"Washington, D.C. : , : International Monetary Fund, , 2012"]
[null,null,"ISBN",null,"1-4755-1037-3"]
[{"$nulls":4},"1-4755-1431-X"]
[null,null,"Descrizione fisica",null,"1 online resource (44 p.)"]
[null,null,"Collana",null,"IMF Working Papers"]
[null,null,"Soggetti",null,"State bonds - Econometric models"]
[{"$nulls":4},"Government securities - Econometric models"]
[{"$nulls":4},"Banks and Banking"]
[{"$nulls":4},"Finance: General"]
[{"$nulls":4},"Investments: Bonds"]
[{"$nulls":4},"International Finance Forecasting and Simulation"]
[{"$nulls":4},"Financial Forecasting and Simulation"]
[{"$nulls":4},"Interest Rates: Determination, Term Structure, and Effects"]
[{"$nulls":4},"General Financial Markets: General (includes Measurement and Data)"]
[{"$nulls":4},"Finance"]
[{"$nulls":4},"Investment & securities"]
[{"$nulls":4},"Yield curve"]
[{"$nulls":4},"Sovereign bonds"]
[{"$nulls":4},"Emerging and frontier financial markets"]
[{"$nulls":4},"Bond yields"]
[{"$nulls":4},"Securities markets"]
[{"$nulls":4},"Financial services"]
[{"$nulls":4},"Financial institutions"]
[{"$nulls":4},"Financial markets"]
[{"$nulls":4},"Interest rates"]
[{"$nulls":4},"Bonds"]
[{"$nulls":4},"Financial services industry"]
[{"$nulls":4},"Capital market"]
[{"$nulls":4},"United States"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Cover; Contents; I. Introduction; II. Literature; III. The data; A. Emerging Market Sovereign Bond Spreads Data; B. Pull Factors Data; Political Risk Rating (PRR); Economic Risk Rating (ERR); Financial Risk Rating (FRR); C. Push Factors Data; IV. The Model; V. Regression Results; A. Baseline regression; B. Global Abundant Liquidity and Global Financial Crisis; Tables; Table 1. Sovereign Bond Spreads: Coefficient Estimates, All Emerging Market Economies; C. Regional Subgroups; D. How Do Fitted Bond Spreads Compare With Actual Bond Spreads?"]
[{"$nulls":4},"Table 2. Sovereign Bond Spreads: Coefficient Estimates Across EM Regions.Figures; Panel 1. Actual and Fitted Sovereign Bond Spreads (basis points); Panel 2. Actual and Fitted Sovereign Bond Spreads: (basis points); E. Robustness Checks; Table 3. Sovereign Bond Spreads: Coefficient Estimates, Robustness Checks; Panel 3. Actual and Fitted Sovereign Bond Spreads (Basis points); F. Simulating an Improvement in Country-specific Variables on Bond Spreads; Table 4. Impact of one-standard deviation change on the model spread (Percent)"]
[{"$nulls":4},"Panel 4. Impact on the Model Spread Provoked by a One-standard Deviation ChangeVI. Back-testing the Model; A. Linear Prediction Method; B. Rolling Regression Method; Table 5. Probabilities that the linear prediction method correctly predicts (i) the; Table 6. Probabilities that the rolling regression (RR1) method correctly predicts; C. Comparing Competing Forecasts; Table 7. Measuring the accuracy of bond spread forecasts with the Diebold-Mariano; VII. Concluding Remarks; References; Appendixes; A. Tables; Appendix Tables"]
[{"$nulls":4},"Table A1. Probabilities that the rolling regression (RR2) method correctly predictsTable A2. Comparing rolling regression and linear prediction forecasts with the Diebold- Mariano test; Table A3. Mean Square Error, Mean Absolute Error and Theil's U Statistics for the rolling regression (RR1) method; Table A4. Mean Square Error, Mean Absolute Error and Theil's U Statistics for the rolling regression (RR2) method; B. Charts; Panel A1. Emerging Market Sovereign Bond Spreads: Actual, Fitted and Residuals; Panel A2: Emerging Markets Sovereign Bond Spread Tracker: January 1998 - December 2001"]
[{"$nulls":4},"Panel A3: Emerging Markets Sovereign Bond Spread Tracker: January 2002 - December 2005Panel A4: Emerging Markets Sovereign Bond Spread Tracker: January 2006 - December 2009; Panel A5: Emerging Markets Sovereign Bond Spread Tracker: January 2010 - December 2011"]
[null,null,null,"Sommario/riassunto","We estimate sovereign bond spreads of 28 emerging economies over the period January 1998-December 2011 and test the ability of the model in generating accurate in-sample predictions for emerging economies bond spreads. The impact and significance of country-specific and global explanatory variables on bond spreads varies across regions, as well as economic periods. During crisis times, good macroeconomic fundamentals are helpful in containing bond spreads, but less than in non-crisis times, possibly reflecting the impact of extra-economic forces on bond spreads when a financial crisis occurs. For some emerging economies, in-sample predictions of the monthly changes in bond spreads obtained with rolling regression routines are significantly more accurate than forecasts obtained with a random walk. Rolling regression-based bond spread predictions appear to convey more information than those obtained with a linear prediction method. By contrast, bond spreads forecasts obtained with a linear prediction method are less accurate than those obtained with random guessing."]