IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v47y2014i3p1147-1172.html
   My bibliography  Save this article

Regional inflation dynamics using space–time models

Author

Listed:
  • Helena Marques
  • Gabriel Pino
  • Juan Dios Tena Horrillo

Abstract

This article provides empirical evidence of the role of spatial factors on the determination of inflation dynamics for a representative set of tradable commodities in Chile. We present a simple model that explains inflation divergence across regions in a monetary union with similar preferences as a consequence of the geographical allocation of producers in the different regions. Our results indicate that spatial allocation together with transport costs are important determinants of regional inflation, while macroeconomic common factors do not play an important role in this process. Existing literature had obtained the opposite result for Europe, and the reasons for this difference warrant further investigation. Moreover, we find that geographical distance seems to be a more appropriate measure of neighbourhood than the adjacency of regions. Our results are robust to different specifications, regression methods and product groupings. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Helena Marques & Gabriel Pino & Juan Dios Tena Horrillo, 2014. "Regional inflation dynamics using space–time models," Empirical Economics, Springer, vol. 47(3), pages 1147-1172, November.
    • Handle: RePEc:spr:empeco:v:47:y:2014:i:3:p:1147-1172
    DOI: 10.1007/s00181-013-0763-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00181-013-0763-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00181-013-0763-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Obstfeld, Maurice & Rogoff, Kenneth, 1995. "Exchange Rate Dynamics Redux," Journal of Political Economy, University of Chicago Press, vol. 103(3), pages 624-660, June.
    2. Juan de Dios Tena & Antoni Espasa & Gabriel Pino, 2010. "Forecasting Spanish Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas," International Regional Science Review, , vol. 33(2), pages 181-204, April.
    3. Culver, Sarah E & Papell, David H, 1997. "Is There a Unit Root in the Inflation Rate? Evidence from Sequential Break and Panel Data Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(4), pages 435-444, July-Aug..
    4. Fujita, Masahisa & Krugman, Paul, 1995. "When is the economy monocentric?: von Thunen and Chamberlin unified," Regional Science and Urban Economics, Elsevier, vol. 25(4), pages 505-528, August.
    5. Jean Boivin & Marc P. Giannoni & Ilian Mihov, 2009. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," American Economic Review, American Economic Association, vol. 99(1), pages 350-384, March.
    6. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    7. Stephen G. Cecchetti & Nelson C. Mark & Robert J. Sonora, 2002. "Price Index Convergence Among United States Cities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1081-1099, November.
    8. Masahisa Fujita & Paul Krugman & Anthony J. Venables, 2001. "The Spatial Economy: Cities, Regions, and International Trade," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262561476, December.
    9. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    10. Kirstin Hubrich & Guenter Beck & Massimiliano Marcellino, 2000. "Regional Inflation Dynamics within and across Euro Area Countries and a Comparison with the US," Regional and Urban Modeling 283600037, EcoMod.
    11. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    12. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    13. Guenter W. Beck & Kirstin Hubrich & Massimiliano Marcellino, 2016. "On the Importance of Sectoral and Regional Shocks for Price‐Setting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1234-1253, November.
    14. Altissimo, Filippo & Benigno, Pierpaolo & Rodriguez Palenzuela, Diego, 2005. "Long-Run Determinants of Inflation Differentials in a Monetary Union," CEPR Discussion Papers 5149, C.E.P.R. Discussion Papers.
    15. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
    16. David C. Parsley & Shang-Jin Wei, 1996. "Convergence to the Law of One Price Without Trade Barriers or Currency Fluctuations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(4), pages 1211-1236.
    17. David M. Drukker & Ingmar Prucha & Rafal Raciborski, 2013. "Maximum likelihood and generalized spatial two-stage least-squares estimators for a spatial-autoregressive model with spatial-autoregressive disturbances," Stata Journal, StataCorp LP, vol. 13(2), pages 221-241, June.
    18. Andrés, Javier & Ortega, Eva & Vallés, Javier, 2008. "Competition and inflation differentials in EMU," Journal of Economic Dynamics and Control, Elsevier, vol. 32(3), pages 848-874, March.
    19. Piras, Gianfranco, 2010. "sphet: Spatial Models with Heteroskedastic Innovations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i01).
    20. Maćkowiak, Bartosz & Moench, Emanuel & Wiederholt, Mirko, 2009. "Sectoral price data and models of price setting," Journal of Monetary Economics, Elsevier, vol. 56(S), pages 78-99.
    21. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26.
    22. Krugman, Paul, 1995. "Innovation and agglomeration: Two parables suggested by city-size distributions," Japan and the World Economy, Elsevier, vol. 7(4), pages 371-390, November.
    23. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nagayasu, Jun, 2014. "Regional inflation, spatial location and the Balassa-Samuelson effect," MPRA Paper 59220, University Library of Munich, Germany.
    2. Gabriel Pino & Subhash C. Sharma, 2019. "On the Contagion Effect in the US Banking Sector," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(1), pages 261-280, February.
    3. Harry Aginta, 2021. "Spatial dynamics of consumer price in Indonesia: convergence clubs and conditioning factors," Asia-Pacific Journal of Regional Science, Springer, vol. 5(2), pages 427-451, June.
    4. Diego Winkelried & José Enrique Gutierrez, 2015. "Regional inflation dynamics and inflation targeting. The case of Peru," Journal of Applied Economics, Universidad del CEMA, vol. 18, pages 199-224, November.
    5. Nagayasu, Jun, 2017. "Inflation and consumption of nontradable goods: Global implications from regional analyses," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 478-491.
    6. Kabukçuoğlu, Ayşe & Martínez-García, Enrique, 2018. "Inflation as a global phenomenon—Some implications for inflation modeling and forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 46-73.
    7. Jun Nagayasu, 2017. "Regional inflation, spatial locations and the Balassa-Samuelson effect: Evidence from Japan," Urban Studies, Urban Studies Journal Limited, vol. 54(6), pages 1482-1499, May.

    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. Kirstin Hubrich & Guenter Beck & Massimiliano Marcellino, 2000. "Regional Inflation Dynamics within and across Euro Area Countries and a Comparison with the US," Regional and Urban Modeling 283600037, EcoMod.
    2. Aleksandra Halka & Grzegorz Szafranski, 2018. "What Common Factors are Driving Inflation in CEE Countries?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(2), pages 131-148.
    3. Eric Girardin & Cheikh A. T. Sall, 2018. "Inflation Dynamics of Franc-Zone Countries Determinants, Co-movements and Spatial Interactions," Open Economies Review, Springer, vol. 29(2), pages 295-320, April.
    4. Peter Tillmann, 2013. "Inflation Targeting and Regional Inflation Persistence: Evidence from Korea," Pacific Economic Review, Wiley Blackwell, vol. 18(2), pages 147-161, May.
    5. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    6. Kaufmann, Daniel & Lein, Sarah M., 2013. "Sticky prices or rational inattention – What can we learn from sectoral price data?," European Economic Review, Elsevier, vol. 64(C), pages 384-394.
    7. Guenter W. Beck & Kirstin Hubrich & Massimiliano Marcellino, 2016. "On the Importance of Sectoral and Regional Shocks for Price‐Setting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1234-1253, November.
    8. Elena Deryugina & Natalia Karlova & Alexey Ponomarenko & Anna Tsvetkova, 2019. "The role of regional and sectoral factors in Russian inflation developments," Economic Change and Restructuring, Springer, vol. 52(4), pages 453-474, November.
    9. Mesbah Motamed & Raymond Florax & William Masters, 2014. "Agriculture, transportation and the timing of urbanization: Global analysis at the grid cell level," Journal of Economic Growth, Springer, vol. 19(3), pages 339-368, September.
    10. Roger Bivand & Giovanni Millo & Gianfranco Piras, 2021. "A Review of Software for Spatial Econometrics in R," Mathematics, MDPI, vol. 9(11), pages 1-40, June.
    11. Kelchtermans, Stijn & Neicu, Daniel & Teirlinck, Peter, 2020. "The role of peer effects in firms’ usage of R&D tax exemptions," Journal of Business Research, Elsevier, vol. 108(C), pages 74-91.
    12. Juan de Dios Tena & Antoni Espasa & Gabriel Pino, 2010. "Forecasting Spanish Inflation Using the Maximum Disaggregation Level by Sectors and Geographical Areas," International Regional Science Review, , vol. 33(2), pages 181-204, April.
    13. Nagayasu, Jun & Inakura, Noriko, 2009. "PPP: Further evidence from Japanese regional data," International Review of Economics & Finance, Elsevier, vol. 18(3), pages 419-427, June.
    14. Tena Horrillo, Juan de Dios & Espasa, Antoni & Pino, Gabriel, 2008. "Forecasting Spanish inflation using information from different sectors and geographical areas," DES - Working Papers. Statistics and Econometrics. WS ws080101, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Michael Roos, 2006. "Regional price levels in Germany," Applied Economics, Taylor & Francis Journals, vol. 38(13), pages 1553-1566.
    16. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
    17. Pino, Gabriel & Tena Horrillo, Juan de Dios & Espasa, Antoni, 2013. "Forecasting disaggregates by sectors and regions : the case of inflation in the euro area and Spain," DES - Working Papers. Statistics and Econometrics. WS ws130807, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Josep LluIs Carrion-I-Silvestre & Tomas Del Barrio & Enrique Lopez-Bazo, 2004. "Evidence on the purchasing power parity in a panel of cities," Applied Economics, Taylor & Francis Journals, vol. 36(9), pages 961-966.
    19. Cantelmo, Alessandro & Melina, Giovanni, 2018. "Monetary policy and the relative price of durable goods," Journal of Economic Dynamics and Control, Elsevier, vol. 86(C), pages 1-48.
    20. Das, Samarjit & Bhattacharya, Kaushik, 2004. "Price Convergence across Regions in India," Bonn Econ Discussion Papers 1/2005, University of Bonn, Bonn Graduate School of Economics (BGSE).

    More about this item

    Keywords

    Regional inflation dynamics; Space–time models; Common factors; Chile; E31; E52; E58; R11; C23; C21;
    All these keywords.

    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

    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:spr:empeco:v:47:y:2014:i:3:p:1147-1172. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.