Understanding and comparing factor-based forecasts:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge, Mass.
National Bureau of Economic Research
2005
|
| Series: | National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series
11285 |
| Subjects: | |
| Abstract: | "Forecasting using 'diffusion indices' has received a good deal of attention in recent years. The idea is to use the common factors estimated from a large panel of data to help forecast the series of interest. This paper assesses the extent to which the forecasts are influenced by (i) how the factors are estimated, and/or (ii) how the forecasts are formulated. We find that for simple data generating processes and when the dynamic structure of the data is known, no one method stands out to be systematically good or bad. All five methods considered have rather similar properties, though some methods are better in long horizon forecasts, especially when the number of time series observations is small. However, when the dynamic structure is unknown and for more complex dynamics and error structures such as the ones encountered in practice, one method stands out to have smaller forecast errors. This method forecasts the series of interest directly, rather than the common and idiosyncratic components separately, and it leaves the dynamics of the factors unspecified. By imposing fewer constraints, and having to estimate a smaller number of auxiliary parameters, the method appears to be less vulnerable to misspecification, leading to improved forecasts"--National Bureau of Economic Research web site. |
| Physical Description: | 27 S. |
Staff View
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| 490 | 1 | |a National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series |v 11285 | |
| 520 | 3 | |a "Forecasting using 'diffusion indices' has received a good deal of attention in recent years. The idea is to use the common factors estimated from a large panel of data to help forecast the series of interest. This paper assesses the extent to which the forecasts are influenced by (i) how the factors are estimated, and/or (ii) how the forecasts are formulated. We find that for simple data generating processes and when the dynamic structure of the data is known, no one method stands out to be systematically good or bad. All five methods considered have rather similar properties, though some methods are better in long horizon forecasts, especially when the number of time series observations is small. However, when the dynamic structure is unknown and for more complex dynamics and error structures such as the ones encountered in practice, one method stands out to have smaller forecast errors. This method forecasts the series of interest directly, rather than the common and idiosyncratic components separately, and it leaves the dynamics of the factors unspecified. By imposing fewer constraints, and having to estimate a smaller number of auxiliary parameters, the method appears to be less vulnerable to misspecification, leading to improved forecasts"--National Bureau of Economic Research web site. | |
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| id | DE-604.BV020045573 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T12:10:54Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-013366582 |
| oclc_num | 60504573 |
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| owner_facet | DE-703 DE-19 DE-BY-UBM |
| physical | 27 S. |
| publishDate | 2005 |
| publishDateSearch | 2005 |
| publishDateSort | 2005 |
| publisher | National Bureau of Economic Research |
| record_format | marc |
| series | National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series |
| series2 | National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series |
| spelling | Boivin, Jean 1972- Verfasser (DE-588)128650761 aut Understanding and comparing factor-based forecasts Jean Boivin ; Serena Ng Cambridge, Mass. National Bureau of Economic Research 2005 27 S. txt rdacontent n rdamedia nc rdacarrier National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series 11285 "Forecasting using 'diffusion indices' has received a good deal of attention in recent years. The idea is to use the common factors estimated from a large panel of data to help forecast the series of interest. This paper assesses the extent to which the forecasts are influenced by (i) how the factors are estimated, and/or (ii) how the forecasts are formulated. We find that for simple data generating processes and when the dynamic structure of the data is known, no one method stands out to be systematically good or bad. All five methods considered have rather similar properties, though some methods are better in long horizon forecasts, especially when the number of time series observations is small. However, when the dynamic structure is unknown and for more complex dynamics and error structures such as the ones encountered in practice, one method stands out to have smaller forecast errors. This method forecasts the series of interest directly, rather than the common and idiosyncratic components separately, and it leaves the dynamics of the factors unspecified. By imposing fewer constraints, and having to estimate a smaller number of auxiliary parameters, the method appears to be less vulnerable to misspecification, leading to improved forecasts"--National Bureau of Economic Research web site. Economic forecasting Statistical methods Ng, Serena 1959- Verfasser (DE-588)12865080X aut National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series 11285 (DE-604)BV002801238 11285 |
| spellingShingle | Boivin, Jean 1972- Ng, Serena 1959- Understanding and comparing factor-based forecasts National Bureau of Economic Research <Cambridge, Mass.>: NBER working paper series Economic forecasting Statistical methods |
| title | Understanding and comparing factor-based forecasts |
| title_auth | Understanding and comparing factor-based forecasts |
| title_exact_search | Understanding and comparing factor-based forecasts |
| title_full | Understanding and comparing factor-based forecasts Jean Boivin ; Serena Ng |
| title_fullStr | Understanding and comparing factor-based forecasts Jean Boivin ; Serena Ng |
| title_full_unstemmed | Understanding and comparing factor-based forecasts Jean Boivin ; Serena Ng |
| title_short | Understanding and comparing factor-based forecasts |
| title_sort | understanding and comparing factor based forecasts |
| topic | Economic forecasting Statistical methods |
| topic_facet | Economic forecasting Statistical methods |
| volume_link | (DE-604)BV002801238 |
| work_keys_str_mv | AT boivinjean understandingandcomparingfactorbasedforecasts AT ngserena understandingandcomparingfactorbasedforecasts |