IDEAS home Printed from https://ideas.repec.org/p/eei/rpaper/eeri_rp_2003_06.html
   My bibliography  Save this paper

The P* model as a general identity to analyze and forecast the behavior of the inflation rate in the economy of Puerto Rico

Author

Listed:
  • Carlos A. Rodríguez Ramos

Abstract

In this work the P* model is used to analyze and forecast the inflation rate in the economy of Puerto Rico. This model is based on two essential points: the first one is to identify the inflationary potential of an economic system through the estimation of the price level to which the inflation tends to adjust in the long run. The second, points that the price level will be adjust, in the long run, to the forecast of the model. Given the way in which the monetary sector in Puerto Rico its constituted, the model needs to complement with U.S.A. monetary variables , such as, monetary supply, to forecast the inflation. The results indicate a long run relationship between the monetary supply of United States (M1) and the price level, the real production and the island s preferential interest rate. The final model is a good representation of the generating process of information (GPI) and it could be used for forecasting purposes. The same predicts the development of inflation better than the two ARIMA models previously selected.

Suggested Citation

  • Carlos A. Rodríguez Ramos, 2003. "The P* model as a general identity to analyze and forecast the behavior of the inflation rate in the economy of Puerto Rico," EERI Research Paper Series EERI_RP_2003_06, Economics and Econometrics Research Institute (EERI), Brussels.
    • Handle: RePEc:eei:rpaper:eeri_rp_2003_06
    as

    Download full text from publisher

    File URL: http://www.eeri.eu/documents/wp/EERI_RP_2003_06.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Galindo, Luis Miguel, 1997. "El modelo P* como indicador de la política monetaria en una economía con alta inflación," El Trimestre Económico, Fondo de Cultura Económica, vol. 64(254), pages 221-239, abril-jun.
    2. Hallman, Jeffrey J & Porter, Richard D & Small, David H, 1991. "Is the Price Level Tied to the M2 Monetary Aggregate in the Long Run?," American Economic Review, American Economic Association, vol. 81(4), pages 841-858, September.
    3. Christian Bordes & Eric Girardin & Velayoudom Marimoutou, 1993. "An Evaluation of the Performance of P-star as an Indicator of Monetary Conditions in the Perspective of EMU: The Case of France," Palgrave Macmillan Books, in: Philip Arestis (ed.), Money and Banking, chapter 12, pages 220-241, Palgrave Macmillan.
    4. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    5. Arnold, Ivo J. M., 1996. "Stochastic trends in the long-run behavior of velocity: A new test of the institutional hypothesis," Journal of Policy Modeling, Elsevier, vol. 18(6), pages 623-641, December.
    6. Hall, Stephen G & Milne, Alistair, 1994. "The Relevance of P-Star Analysis to UK Monetary Policy," Economic Journal, Royal Economic Society, vol. 104(424), pages 597-604, May.
    7. Richard G. Anderson & Jeffrey J. Hallman, 1993. "Has the long-run velocity of M2 shifted? Evidence from the P* model," Economic Review, Federal Reserve Bank of Cleveland, vol. 29(Q I), pages 14-26.
    8. Philip Arestis (ed.), 1993. "Money and Banking," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-349-13319-2, December.
    9. Kenneth N. Kuttner, 1989. "Monetary and non-monetary sources of inflation: an error correction analysis," Working Paper Series, Macroeconomic Issues 89-15, Federal Reserve Bank of Chicago.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carlos A. Rodríguez Ramos, 2003. "The P* model as a general identity to analyze and forecast the behavior of the inflation rate in the economy of Puerto Rico," Econometrics 0302002, University Library of Munich, Germany.
    2. Rodríguez, Carlos A., 2004. "A P* Model of Inflation in Puerto Rico," MPRA Paper 41278, University Library of Munich, Germany.
    3. Mamoon, Dawood & Nicholas, Howard, 2017. "Financial Liberalisation and Economic Growth: A Preliminary Analysis," MPRA Paper 82976, University Library of Munich, Germany.
    4. Jansen, Eilev S., 2004. "Modelling inflation in the euro area," Working Paper Series 322, European Central Bank.
    5. Takeshi Kimura & Hiroshi Kobayashi & Jun Muranaga & Hiroshi Ugai, 2003. "The effect of the increase in the monetary base of Japan's economy at zero interest rates: an empirical analysis," BIS Papers chapters, in: Bank for International Settlements (ed.), Monetary policy in a changing environment, volume 19, pages 276-312, Bank for International Settlements.
    6. Helmut Herwartz & Hans‐Eggert Reimers, 2006. "Long‐Run Links among Money, Prices and Output: Worldwide Evidence," German Economic Review, Verein für Socialpolitik, vol. 7(1), pages 65-86, February.
    7. Ivars Tillers, 2004. "Money Demand in Latvia," Working Papers 2004/03, Latvijas Banka.
    8. Ericsson, Neil R & Hendry, David F & Mizon, Grayham E, 1998. "Exogeneity, Cointegration, and Economic Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 370-387, October.
    9. Stephen Hall & David Shepherd, 2003. "Testing for Common Cycles in Money, Nominal Income and Prices," Manchester School, University of Manchester, vol. 71(s1), pages 68-84, September.
    10. Thirtle, C. & Townsend, R. & van Zyl, J., 1998. "Testing the induced innovation hypothesis: an error correction model of South African agriculture," Agricultural Economics, Blackwell, vol. 19(1-2), pages 145-157, September.
    11. Czudaj, Robert, 2011. "P-star in times of crisis - Forecasting inflation for the euro area," Economic Systems, Elsevier, vol. 35(3), pages 390-407, September.
    12. Naser, Hanan, 2014. "On the cointegration and causality between Oil market, Nuclear Energy Consumption, and Economic Growth: Evidence from Developed Countries," MPRA Paper 65252, University Library of Munich, Germany, revised 25 Mar 2015.
    13. Liang, Qi & Teng, Jian-Zhou, 2006. "Financial development and economic growth: Evidence from China," China Economic Review, Elsevier, vol. 17(4), pages 395-411.
    14. Barnett, William A. & Su, Liting, 2015. "The Use of Divisia Monetary Aggregates in Nominal GDP Targeting," MPRA Paper 67040, University Library of Munich, Germany.
    15. Pablo García S. & Rodrigo Valdés P, 2003. "Dinero e Inflación en el Marco de Metas de Inflación," Working Papers Central Bank of Chile 198, Central Bank of Chile.
    16. Dierk Herzer & Holger Strulik & Sebastian Vollmer, 2012. "The long-run determinants of fertility: one century of demographic change 1900–1999," Journal of Economic Growth, Springer, vol. 17(4), pages 357-385, December.
    17. Ansgar Belke & Thorsten Polleit, 2004. "A Model for Forecasting Swedish Inflation," Diskussionspapiere aus dem Institut für Volkswirtschaftslehre der Universität Hohenheim 246/2004, Department of Economics, University of Hohenheim, Germany.
    18. Herzer, Dierk, 2013. "Cross-Country Heterogeneity and the Trade-Income Relationship," World Development, Elsevier, vol. 44(C), pages 194-211.
    19. J.M. Groeneveld & K.G. Koedijk & C.J.M. Kool, 1997. "Money, prices and the transition to EMU," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 50(203), pages 481-504.
    20. Scharnagl, Michael, 1996. "Monetary aggregates with special reference to structural changes in the financial markets," Discussion Paper Series 1: Economic Studies 1996,02e, Deutsche Bundesbank.

    More about this item

    Keywords

    Econometric Modeling; Time Series Analysis; Forecasting Methods; Monetary Economics.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eei:rpaper:eeri_rp_2003_06. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Julia van Hove (email available below). General contact details of provider: https://edirc.repec.org/data/eeriibe.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.