LATCOIN: Determining Medium to Long-Run Tendencies of Economic Growth in Latvia in Real Time
AbstractThis paper presents a method of estimating the current state of Latvia's economy. The evaluation object is medium to long-run growth of real GDP, but not actual GDP itself, which helps to filter out various one-off effects and focus on medium and long-run tendencies. Our indicator, called LATCOIN (Latvia's Business Cycle Coincidence Indicator), could be viewed as a simple adaptation of EUROCOIN for Latvia with some changes in methodology. LATCOIN is a monthly estimate of the medium to long-run growth of Latvia's real GDP, which is produced on the 9th working day of the next month. Using a large panel of macroeconomic variables, few smooth unobservable factors describing the economy are constructed. Further, these factors are used for the estimation of LATCOIN.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Latvijas Banka in its series Working Papers with number 2010/01.
Date of creation: 25 Jan 2010
Date of revision:
Latvia's real GDP; band-pass filter; coincidence indicator; generalised principal components; real-time performance; turning points;
Other versions of this item:
- Konstantīns Beņkovskis, 2010. "LATCOIN: determining medium to long-run tendencies of economic growth in Latvia in real time," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 10(2), pages 27-48, December.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005.
"The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting,"
Journal of the American Statistical Association,
American Statistical Association, vol. 100, pages 830-840, September.
- Forni M. & Hallin M., 2003. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Computing in Economics and Finance 2003 143, Society for Computational Economics.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2005. "The generalised dynamic factor model: one sided estimation and forecasting," ULB Institutional Repository 2013/10129, ULB -- Universite Libre de Bruxelles.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2002. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," CEPR Discussion Papers 3432, C.E.P.R. Discussion Papers.
- Lawrence J. Christiano & Terry J. Fitzgerald, 1999.
"The Band pass filter,"
9906, Federal Reserve Bank of Cleveland.
- Jushan Bai & Serena Ng, 2000.
"Determining the Number of Factors in Approximate Factor Models,"
Boston College Working Papers in Economics
440, Boston College Department of Economics.
- Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
- Aleksejs Melihovs & Svetlana Rusakova, 2005. "Short-Term Forecasting of Economic Development in Latvia Using Business and Consumer Survey Data," Working Papers 2005/04, Latvijas Banka.
- Marianne Baxter & Robert G. King, 1999.
"Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series,"
The Review of Economics and Statistics,
MIT Press, vol. 81(4), pages 575-593, November.
- Tom Doan, . "BKFILTER: RATS procedure to implement band pass filter using Baxter-King method," Statistical Software Components RTS00026, Boston College Department of Economics.
- Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
- Viktors Ajevskis & Gundars Davidsons, 2008. "Dynamic Factor Models in Forecasting Latvia's Gross Domestic Product," Working Papers 2008/02, Latvijas Banka.
- Konstantins Benkovskis, 2008. "Short-Term Forecasts of Latvia's Real Gross Domestic Product Growth Using Monthly Indicators," Working Papers 2008/05, Latvijas Banka.
- Ginters Buss, 2012. "Forecasting and Signal Extraction with Regularised Multivariate Direct Filter Approach," Working Papers 2012/06, Latvijas Banka.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ivars Tillers).
If references are entirely missing, you can add them using this form.