Quality & Quantity

, Volume 51, Issue 3, pp 1417–1434 | Cite as

How does inflation determine inflation uncertainty? A Chinese perspective

  • Chi-Wei Su
  • Hui Yu
  • Hsu-Ling Chang
  • Xiao-Lin LiEmail author


Using a bootstrap Granger full-sample causality test and a sub-sample rolling window estimation, this paper examines the causal link between inflation and inflation uncertainty in China. The results show that high inflation leads to high inflation uncertainty, supporting Friedman-Ball’s hypothesis (1992) and Holland’s theory (J Money Credit Bank 27:827–837, 1995). Furthermore, significant feedback exists from inflation uncertainty to inflation in some periods, supporting Holland’s theory (J Money Credit Bank 27:827–837, 1995) that inflation uncertainty has a negative effect on inflation. We find that the relationship between inflation and inflation uncertainty varies across time. The Chinese monetary authority needs to ensure a quick and effective policy response to inflation development because doing so will help reduce inflation, eliminate many of the costs associated with high inflation and therefore minimize the marginal effect of inflation on inflation uncertainty. However, quantitative tools for China’s monetary policy are also warranted. In the long term, the importance of keeping inflation low, stable, and predictable cannot be overemphasized.


Inflation Inflation uncertainty Rolling window Bootstrap Time-varying causality GJR-GARCH 

JEL Classification

C22 E31 



This research is supported by the National Social Science Foundation (Grant number: 15BJY155), and Ministry of Education’s Humanities and Social Science Research Project (Grant number: 14YJA790049).


  1. Andrews, K.: Tests for parameter instability and structural change with unknown change point. Econometrica 61, 821–856 (1993)Google Scholar
  2. Andrews, K., Ploberger, W.: Optimal tests when a nuisance parameter is present only under the alternative. Econometrica 62, 1383–1414 (1994)Google Scholar
  3. Baillie, R., Chung, C., Tiesau, M.: Analyzing inflation by the fractionally integrated ARFIMA-GARCH model. J. Appl. Econom. 11, 23–40 (1996)Google Scholar
  4. Ball, L.: Why does high inflation raise inflation uncertainty? J. Monet. Econ. 29, 371–388 (1992)Google Scholar
  5. Balcilar, M., Ozdemir, A., Arslanturk, Y.: Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window. Energy Econ. 32, 1398–1410 (2010)Google Scholar
  6. Balcilar, M., Ozdemir, A.: Asymmetric and time-varying causality between inflation and inflation uncertainty in G-7 countries. Scott. J. Political Econ. 60, 99–125 (2013)Google Scholar
  7. Bierens, H.: Testing the unit root with drift hypothesis against nonlinear trend stationarity with an application to the U interest rate. J. Econom. 81, 29–64 (1997)Google Scholar
  8. Bollerslev, T.: Generalized autoregressive conditional heteroskedasticity. J. Econ. 31, 307–327 (1986)Google Scholar
  9. Bredin, D., Fountas, S.: US inflation and inflation uncertainty in a historical perspective: the impact of recessions. UCD Geary Institute, working paper No. 201053 (2010)Google Scholar
  10. Brunner, A., Hess, G.: Are higher levels of inflation less predictable? A state- dependent conditional heteroscedasticity approach. J. Bus. Econ. Stat. 11, 187–197 (1993)Google Scholar
  11. Campell, J., Hentschell, L.: No news is good news: an asymmetric model of changing volatility in stock returns. J. Finance Econ. 31, 281–318 (1992)Google Scholar
  12. Chen, S., Shen, C.: Evidence of a nonlinear relationship between inflation and inflation uncertainty: the case of the four little dragons. J. Policy Model. 30, 363–376 (2008)Google Scholar
  13. Chowdhury, A.: Inflation and inflation-uncertainty in India: the policy implications of the relationship. J. Econ. Study 41(1), 71–86 (2014)Google Scholar
  14. Conrad, C., Karanasos, M.: The impulse response function of the long memory GARCH process. Econ. Lett. 90, 34–41 (2005)Google Scholar
  15. Crawford, A., Kasumovich, M.: Does inflation uncertainty vary with the level of inflation? Bank of Canada, Ottawa Ontario Canada K1A 0G9 (1996)Google Scholar
  16. Cukierman, A., Meltzer, A.: A theory of ambiguity, credibility, and inflation under discretion and asymmetric information. Econometrics 54, 1099–1128 (1986)Google Scholar
  17. Dai, M., Spyromitros, E.: Inflation contract, central bank transparency and model uncertainty. Econ. Model. 29, 2371–2381 (2012)Google Scholar
  18. Dhamija, A., Bhalla, V.: Financial time series forecasting: comparison of neural networks and ARCH models. Int. Res. J. Finance Econ. 49, 194–212 (2010)Google Scholar
  19. Dickey, A., Fuller, A.: Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49, 1057–1072 (1981)Google Scholar
  20. Ding, J., et al.: A long memory property of stock market returns and a new model. J. Empir. Finance 1, 83–106 (1993)Google Scholar
  21. Duan, J.: The GARCH option pricing model. Math. Finance 5, 13–32 (1995)Google Scholar
  22. Eksi, O.: Endogenous markups in the new Keynesian model: implications for inflation-output trade-off and welfare. Econ. Model. 51, 626–634 (2015)Google Scholar
  23. Engle, F.: Estimates of the variance of U.S. inflation based on the ARCH model. J. Money Credit Bank. 15, 286–301 (1983)Google Scholar
  24. Engle, R., Lee, G.: A permanent and transitory component model of stock return volatility. In: Engle, Robert F., White, Halbert L. (eds.) Cointegration, Causality, and forecasting: a festschrift in honor of Clive W. J. Granger. Oxford University Press, New York (1999)Google Scholar
  25. Evans, M., Wachtel, P.: Inflation regimes and the sources of inflation uncertainty. J. Money Credit Bank. 25, 475–511 (1993)Google Scholar
  26. Fang, W., Miller, S., Lee, C.: Cross-country evidence on output growth volatility: nonstationary variance and GARCH models. Scott. J. Polit. Econ. 55(4), 509–541 (2008)Google Scholar
  27. Fornari, F., Mele, A.: Sign- and volatility-switching ARCH models: theory and applications to international stock markets. J. Appl. Econom. 12, 49–65 (1997)Google Scholar
  28. Fountas, S.: The relationship between inflation and inflation uncertainty in the UK; 1885–1998. Econ. Lett. 74, 77–83 (2001)Google Scholar
  29. Fountas, S., Ioannidis, A., Karanasos, M.: Inflation, inflation uncertainty and a Common European Monetary Policy. Manch. Sch. 72, 221–242 (2004)Google Scholar
  30. Fountas, S., Karansos, M.: Inflation, output growth and nominal and real uncertainty: empirical evidence for the G7. J. Int. Money Finance 26, 229–250 (2007)Google Scholar
  31. Friedman, M.: Nobel lecture: inflation and unemployment. J. Polit. Econ. 85, 451–472 (1977)Google Scholar
  32. Labuschagne, C., Venter, P., Boetticher, S.: A comparison of risk neutral historic distribution-, E-GARCH and GJR-GARCH model generated volatility skews for BRICS securities exchange indexes. Proc. Econ. Finance 24, 344–352 (2015)Google Scholar
  33. Glosten, R.: Relationship between the expected value and the volatility of the nominal excess return on stocks. J. Finance 48(5), 1779–1801 (1993)Google Scholar
  34. Golob, E.: Does inflation uncertainty increase with inflation? Fed Reserve Bank Kans City Econ. Rev. 79, 27–38 (1994)Google Scholar
  35. Granger, J.: Investigating causal relation by econometric and crosssectional method. Econometrica 37, 424–438 (1969)Google Scholar
  36. Granville, B., Mallick, S.: Does inflation or currency depreciation drive monetary policy in Russia? Res. Int. Bus. Finance 20, 163–179 (2006)Google Scholar
  37. Grier, K., Henry, N., Shields, K.: The asymmetric effects of uncertainty on inflation growth. J. Appl. Econom. 19, 551–565 (2004)Google Scholar
  38. Grier, K., Perry, M.: The effects of real and nominal uncertainty on inflation and output growth: some GARCH-M evidence. J. Appl. Econom. 15, 45–58 (2000)Google Scholar
  39. Grier, K., Tullock, G.: An empirical analysis of cross-national economic growth. J. Monet. Econ. 23, 259–276 (1989)Google Scholar
  40. Hacker, S., Hatemi, A.: Tests for causality between integrated variables based on asymptotic and bootstrap distributions: theory and application. Appl. Econ. 38, 1489–1500 (2006)Google Scholar
  41. Hamermesh, D., Rees, A.: The Economics of Work and Pay. HarperCollins Publishers, New York (1984)Google Scholar
  42. Hansen, B.E.: Tests for parameter instability in regressions with I (1) processes. J. Bus. Econ. Stat. 10, 321–336 (1992)Google Scholar
  43. Hentschel, L.: All in the family nesting symmetric and asymmetric GARCH models. J. Finance Econ. 39, 71–104 (1995)Google Scholar
  44. Holland, S.: Does higher inflation lead to more uncertain inflation? Federal Reserve Bank of St. Louis Review. 66, 15–26 (1984)Google Scholar
  45. Holland, S.: Comments on inflation regimes and the sources of inflation uncertainty. J. Money Credit Bank. 25, 514–520 (1993)Google Scholar
  46. Holland, S.: Inflation and uncertainty: tests for temporal ordering. J. Money Credit Bank. 27, 827–837 (1995)Google Scholar
  47. Hou, J.: Economic reform of China: cause and effects. Soc. Sci. J. 48, 419–434 (2011)Google Scholar
  48. Hu, R., Su, Z.: Nonlinear relationship of inflation and inflation uncertainty in China. J. Quant. Tech. Econ. 57, 28–37 (2008)Google Scholar
  49. Huybens, E., Smith, B.: Inflation, financial markets, and long-run real activity. J. Monet. Econ. 43, 283–315 (1999)Google Scholar
  50. Hwang, Y.: Causality between inflation and real growth. Econ. Lett. 73, 179–186 (2007)Google Scholar
  51. Jiranyakul, K., Opiela, T.: Inflation and inflation uncertainty in the ASEAN-5 economies. J. Asian Econ. 21, 105–112 (2010)Google Scholar
  52. Judson, R., Orphanides, O.: Inflation, volatility and growth. Int. Finance 2, 117–138 (1999)Google Scholar
  53. Karahan, O.: The relationship between inflation and inflation uncertainty: evidence from the Turkish economy. Econ. Finance 1, 219–228 (2012)Google Scholar
  54. Kapetanios, G., Shin, Y., Snell, A.: Testing for a unit root in the nonlinear STAR framework. J. Econom. 112, 359–379 (2003)Google Scholar
  55. Kwiatkowski, D., Phillips, B., Schmidt, P., Shin, Y.: Testing the null hypothesis of stationarity against the alternative of a unit root. J. Econ. 54, 159–178 (1992)Google Scholar
  56. Ma, H.: Inflation, uncertainty, and growth in Colombia. IMF Working Paper. 161, 1–28 (1998)Google Scholar
  57. Mantalos, P.: A graphical investigation of the size and power of the granger-causality tests in integrated-cointegrated VAR systems. Stud. Non-Linear Dyn. Econom. 4, 17–33 (2000)Google Scholar
  58. Mallick, S., Mohsin, M.: On the effects of inflation shocks in a small open economy. Aust. Econ. Rev. 40, 253–266 (2007)Google Scholar
  59. Mallick, S., Mohsin, M.: On the real effects of inflation in open economies: theory and empirics. Empir. Econ. 39, 643–673 (2009)Google Scholar
  60. Nelson, D.: Conditional heteroskedasticity in asset returns: a new approach. Econometria 59, 347–370 (1991)Google Scholar
  61. Newey, K., West, D.: Automatic lag selection in covariance matrix estimation. Rev. Econ. Stud. 61, 631–654 (1994)Google Scholar
  62. Nyblom, J.: Testing for the constancy of parameters over time. J. Am. Stat. Assoc. 84, 223–230 (1989)Google Scholar
  63. Okun, A.: The mirage of steady inflation. Brook. Pap. Econ. Act. 2, 485–498 (1971)Google Scholar
  64. Oscorio, C., Unsal, D.: Inflation dynamics in Asia: causes, changes, and spillovers from China. J. Asian Econ. 24, 26–40 (2013)Google Scholar
  65. Perron, P.: The great crash, the oil price shock, and the unit root hypothesis. Econometrica 57(6), 1361–1401 (1989)Google Scholar
  66. Phillips, B., Perron, P.: Testing for a unit root in time series regression. Biometrika 75(2), 335–346 (1988)Google Scholar
  67. Robinson, P.: Efficient tests of nonstationary hypotheses. J. Am. Stat. Assoc. 89, 1420–1437 (1994)Google Scholar
  68. Pourgerami, A., Maskus, K.: The effects of inflation on the predictability of price changes in Latin America: some estimates and policy implications. World Dev. 15, 287–290 (1987)Google Scholar
  69. Sabbatini, M., Linton, O.: A GARCH model of the implied volatility of the Swiss market index from option prices. Int. J. Forecast. 14, 199–213 (1998)Google Scholar
  70. Scharnagl, M., Stapf, J.: Inflation, deflation, and uncertainty: what drives euro-area option-implied inflation expectations, and are they still anchored in the sovereign debt crisis? Econ. Model. 48, 248–269 (2015)Google Scholar
  71. Sims, C.A., Stock, J.H., Watson, M.W.: Inference in linear time series with some unit roots. Econometrica 58(1), 113–144 (1990)Google Scholar
  72. Shukur, G., Mantalos, P.: Size and power of the RESET test as applied to systems of equations: a bootstrap approach. Working paper, Department of Statistics, University of Lund (1997a)Google Scholar
  73. Shukur, G., Mantalos, P.: Tests for Granger causality in integrated-cointegrated VAR systems. Working paper, Department of Statistics, University of Lund, (1997b)Google Scholar
  74. Shukur, G., Mantalos, P.: A simple investigation of the Granger-causality test in integrated-cointegrated VAR systems. J. Appl. Stat. 27, 1021–1031 (2000)Google Scholar
  75. Stock, J., Watson, M.: Has the business cycle changed? Evidence and explanations. Federal Reserve Bank of Kansas City, Kansas City (2003)Google Scholar
  76. Szakmary, A.: The predictive power of implied volatility: evidence from 35 futures markets. J. Bank. Finance 11, 2151–2175 (2003)Google Scholar
  77. Toda, Y., Phillips, B.: Vector autoregressions and causality. Econometrica 61, 1367–1393 (1993)Google Scholar
  78. Toda, Y., Phillips, B.: Vector autoregression and causality: a theoretical overview and simulation study. Econom. Rev. 13, 259–285 (1994)Google Scholar
  79. Toda, Y., Yamamoto, T.: Statistical inference in vector autoregressions with possibly integrated processes. J. Econom. 66, 225–250 (1995)Google Scholar
  80. Thorton, J.: Inflation and inflation uncertainty in Argentina, 1810–2005. Econ. Lett. 98, 247–252 (2008)Google Scholar
  81. Ungar, M., Zilberfarb, B.: Inflation and its unpredictability-theory and empirical evidence. J. Money Credit Bank. 25, 709–720 (1993)Google Scholar
  82. Wilson, K.: The links between inflation, inflation uncertainty and output growth: new time series evidence from Japan. J. Macroecon. 28, 609–620 (2006)Google Scholar
  83. Xiong, W.: Measuring the monetary policy stance of the People’s bank of china: an ordered probit analysis. China Econ. Rev. 23, 512–533 (2012)Google Scholar
  84. Yi, G.: Inflation and price instability: an empirical study of the People’s Republic of China. China Econ. Rev. 1, 155–165 (1990)Google Scholar
  85. Zakoian, M.: Threshold heteroskedastic models. J. Econ. Dyn. Control 18, 931–955 (1994)Google Scholar
  86. Zeileis, A., Leisch, F., Kleiber, C., Hornik, K.: Monitoring structural change in dynamic econometric models. J. Appl. Econ. 20(1), 99–121 (2005)Google Scholar
  87. Zhang, B., Li, X.: The asymmetric behaviour of stock returns and volatilities: evidence from Chinese stock market. Appl. Econ. Lett. 15, 959–962 (2008)Google Scholar
  88. Zhang, C.: China inflation dynamics: persistence and policy regimes. J. Policy Model. 32, 373–388 (2010)Google Scholar
  89. Zhang, C.: Non-parametric determination of real-time lag structure between two time series: the “optimal thermal causal path” method with applications to economic data. China Econ. Rev. 23, 60–70 (2012)Google Scholar
  90. Zhang, C.: Understanding the evolving inflation process in China: 1997–2011. Soc. Sci. J. 50, 331–337 (2013)Google Scholar
  91. Zhou, W.: Non-parametric determination of real-time lag structure between two time series: the “optimal thermal causal path” method with applications to economic data. J. Macroecon. 28, 195–224 (2006)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Chi-Wei Su
    • 1
  • Hui Yu
    • 1
  • Hsu-Ling Chang
    • 2
  • Xiao-Lin Li
    • 1
    Email author
  1. 1.Department of FinanceOcean University of ChinaQingdaoChina
  2. 2.Department of Accounting and InformationLing Tung UniversityTaichungTaiwan

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