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From |
kokootchke <kokootchke@hotmail.com> |

To |
statalist <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Factor models in panel data (was: Factor models) |

Date |
Wed, 14 Oct 2009 18:12:39 -0400 |

<5d309276347f2.4a6a72bd@mail.nyu.edu> <COL111-W615BFF169F6A53D1717D1FD1100@phx.gbl> <6060c8877a3a.4a748757@mail.nyu.edu> <COL111-W15C285D7D68AD1D33BF6F8D10F0@phx.gbl> Content-Type: text/plain; charset="Windows-1252" Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 > From: kokootchke@hotmail.com > To: statalist@hsphsun2.harvard.edu > Subject: RE: st: Factor models in panel data (was: Factor models) > Date: Mon=2C 3 Aug 2009 10:20:48 -0400 >=20 > Thank you=2C Bob. I think the article you suggested is: >=20 > Koopman and Lucas (2008)=2C "A Non-Gaussian Panel Time Series Model for > Estimating and Decomposing Default Risk" >=20 > I am reading it now and it looks useful! (and even if it's not=2C it seem= s like I should be aware of it!) Thank you very much. >=20 > Adrian >=20 >=20 > ---------------------------------------- >> From: bob.yaffee@nyu.edu >> To: statalist@hsphsun2.harvard.edu >> Date: Sat=2C 1 Aug 2009 18:20:07 -0400 >> Subject: Re: st: Factor models in panel data (was: Factor models) >> >> Adrian=2C >> I read an article in the Journal of Business and Economic Statistics a f= ew months ago >> that suggests that State Space models can handle panel data. >> That might be of some help. >> You're quite welcome=2C >> Bob >> >> >> Robert A. Yaffee=2C Ph.D. >> Research Professor >> Silver School of Social Work >> New York University >> >> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf >> >> CV: http://homepages.nyu.edu/~ray1/vita.pdf >> >> ----- Original Message ----- >> From: kokootchke=20 >> Date: Friday=2C July 31=2C 2009 2:58 pm >> Subject: st: Factor models in panel data (was: Factor models) >> To: statalist=20 >> >> >>> First of all=2C thanks to Bob for all the references on dynamic factor = models. >>> >>> I think that some of these are useful for my purposes but not >>> entirely=2C mainly due to the panel structure of my data. >>> >>> As I mentioned earlier=2C I have data on domestic macroeconomic >>> variables for 40+ countries over time (e.g.=2C GDP growth=2C dollar >>> reserves=2C inflation=2C etc.) AND data on global financial conditions >>> that are common to all countries in my data set at any given point in >>> time (e.g.=2C the level of the U.S. interest rate=2C volatility in the >>> EMBI index=2C volatility of the VIX index=2C etc.). >>> >>> The problems I see with the implementation of a standard factor model >>> (as implemented by -factor- in Stata) are the following: >>> >>> 1. I think that=2C as it is=2C this command doesn't take into account t= he >>> panel structure of the database=2C does it? For instance=2C if my data = has >>> 80 quarters per country and 40 countries and it's sorted by country >>> and time period=2C then the change between observation 79 and 80 for an= y >>> given domestic macroeconomic variable is going to be very different >>> than the change between observation 80 and 81=2C because the former two >>> correspond to periods 79 and 80 of country 1=2C while the latter two >>> correspond to period 80 of country 1 and period 1 of country 2. >>> >>> 2. While the domestic macroeconomic variables change by country and by >>> time period (e.g.=2C each country has different inflation rates in 1995 >>> Q2)=2C global financial conditions are the same for all countries at a >>> given time period (e.g.=2C the U.S. interest rate is the same for ALL >>> countries in my data base in 1995 Q2). So=2C can I still put these >>> common variables together in the same database where I have my >>> domestic variables before I do the factor analysis? >>> >>> 3. Some of my variables as I use them in my regression model are in >>> logs (e.g.=2C log of the U.S. interest rate)=2C or "scaled" appropriate= ly >>> to compare them across countries (e.g.=2C reserves/imports=2C external >>> debt/GDP=2C etc.)? Should I leave them like this in my factor analysis= =2C >>> or should I just use the actual variables I'm interested in (e.g.=2C >>> U.S. interest rates in levels=2C reserves and external debt without >>> scaling by imports or GDP=2C respectively=2C etc.)? >>> >>> Thank you very much once again. >>> >>> Adrian >>> >>> >>> ---------------------------------------- >>>> From: bob.yaffee@nyu.edu >>>> To: statalist@hsphsun2.harvard.edu >>>> Date: Sat=2C 25 Jul 2009 02:49:33 -0400 >>>> Subject: Re: st: Factor models >>>> >>>> Adrian=2C >>>> There is a substantial literature on dynamic factor models. Mario >>> Forni and Lucrezia Richlin have written on this in 1996 and 1998 . In >>> September 2003=2C Mario Forni=2C Marc Hallan=2C Marco Lippi=2C and >>>> Lucrezia Richline published "The Generalized Dynamic Factor Model: One= -sided >>>> Estimation and Forecasting=2C" as an LEM working paper (2003/13). >>> Marco Lippi and Daniel Thornton >>>> have written a working paper for the St. Louis Federal Reserve bank >>> (WP2004-013a) in >>>> 2004=2C entitled "A dynamic factor analysis of the response of U.S. >>> interest to News." >>>> Stock and Watson in 1989=2C 1991=2C and later have worked on this >>> subject. In 2005 they >>>> published=2C "Implications of Dynamic Factor models for VAR analysis= =2C" >>> in which they have dealt with dynamic factors and model identification >>> with long and short run restrictions in VAR form. Tao Chen=2C Elaine >>> Martin=2C and Gary Montague have written an article in Computational >>> Statistics and Data Analysis (2009) v. 59 entitled=2C "Robust >>> probabalistic PCA with missing data and contribution for outlier >>> detection." Rangan Gupta and Alain Kabundi in 2008 (Journal of >>> Economic Literature) have written "A Dynamic Factor Analysis for >>> Forecasting Macroeconomic Variables in South Africa." Some >>>> time ago=2C Allessandro Federici and Andrea Mazzitelli in 2005 at an >>> Italian Stata User's Group presented "Dynamic Factor Analysis with >>> Stata=2C" based on the Coppi and Zannella(1978) and later work. >>>> In 2004 Ben Bernanke has written on factor analysis with BVAR >>> models. Siem Jan Koopman has also incorporated PCA in his state space >>> models. James Hamilton=2C in his 1994 classic=2C Time Series Analysis= =2C has >>> shown how state space models lend themselves to dynamic factor analysis= . >>>> And these are small sample of the articles that have emerged on this >>> subject. Andrew Harvey in 1989 in "Forecasting=2C Structural time serie= s >>> models=2C and the Kalman Filter" has also shown on these factors are th= e >>> unobserved signal components extracted from the data generating process= . >>>> These are some of the articles on the subject. >>>> Regards=2C >>>> Bob Yaffee >>>> >>>> >>>> Robert A. Yaffee=2C Ph.D. >>>> Research Professor >>>> Silver School of Social Work >>>> New York University >>>> >>>> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf >>>> >>>> CV: http://homepages.nyu.edu/~ray1/vita.pdf >>>> >>>> ----- Original Message ----- >>>> From: kokootchke >>>> Date: Friday=2C July 24=2C 2009 7:49 pm >>>> Subject: st: Factor models >>>> To: statalist >>>> >>>> >>>>> Hi everyone. >>>>> >>>>> I would like to know if anyone could provide some references to >>>>> factor models (latent factor models=2C dynamic factor models=2C etc.)= . >>>>> >>>>> I am studying the effects of domestic macroeconomic variables vs. >>>>> global economic conditions on bond spreads and I believe that I could >>>>> use factor models to improve my analyses. >>>>> >>>>> I have never used these models before and have found some papers by >>>>> Stock and Watson=2C Lippi et al.=2C etc... which are useful... but I = would >>>>> like to read something a bit easier to get my feet wet=2C and then st= art >>>>> building up from there. >>>>> >>>>> Thank you very much! >>>>> >>>>> Best regards=2C >>>>> Adrian >>>>> >>>>> _________________________________________________________________ >>>>> NEW mobile Hotmail. Optimized for YOUR phone. Click here. >>>>> http://windowslive.com/Mobile?ocid=3DTXT_TAGLM_WL_CS_MB_new_hotmail_0= 72009 >>>>> * >>>>> * For searches and help try: >>>>> * http://www.stata.com/help.cgi?search >>>>> * http://www.stata.com/support/statalist/faq >>>>> * http://www.ats.ucla.edu/stat/stata/ >>>>> >>>> * >>>> * For searches and help try: >>>> * http://www.stata.com/help.cgi?search >>>> * http://www.stata.com/support/statalist/faq >>>> * http://www.ats.ucla.edu/stat/stata/ >>> >>> _________________________________________________________________ >>> Windows Live=99 SkyDrive=99: Store=2C access=2C and share your photos. = See how. >>> http://windowslive.com/Online/SkyDrive?ocid=3DTXT_TAGLM_WL_CS_SD_photos= _072009 >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/statalist/faq >>> * http://www.ats.ucla.edu/stat/stata/ >> >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >=20 > _________________________________________________________________ > Express your personality in color! Preview and select themes for Hotmail= =AE.=20 > http://www.windowslive-hotmail.com/LearnMore/personalize.aspx?ocid=3DPID2= 3391::T:WLMTAGL:ON:WL:en-US:WM_HYGN_express:082009 > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ =0A= _________________________________________________________________=0A= Hotmail: Free=2C trusted and rich email service.=0A= http://clk.atdmt.com/GBL/go/171222984/direct/01/= * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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