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Inflation forecasting models for Uganda: is mobile money relevant?

Author

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  • Muellbauer, John
  • Aron, Janine
  • Sebudde, Rachel

Abstract

Forecasting inflation is challenging in emerging markets, where trade and monetary regimes have shifted, and the exchange rate, energy and food prices are highly volatile. Mobile money is a recent financial innovation giving financial transaction services via a mobile phone, including to the unbanked. Stable models for the 1-month and 3-month-ahead rates of inflation in Uganda, measured by the consumer price index for food and non-food, and for the domestic fuel price, are estimated over 1994-2013. Key features are the use of multivariate models with equilibrium-correction terms in relative prices; introducing non-linearities to proxy state dependence in the inflation process; and applying a ?parsimonious longer lags? (PLL) parameterisation to feature lags up to 12 months. International influences through foreign prices and the exchange rate (including food prices in Kenya after regional integration) have an important influence on the dependent variables, as does the growth of domestic credit. Rainfall deviation from the long-run mean is an important driver for all, most dramatically for food. The domestic money stock is irrelevant for food and fuel inflation, but has a small effect on non-food inflation. Other drivers include the trade and current account balances, fiscal balance, terms of trade and trade openness, and the international interest rate differential. Parameter stability tests suggest the models could be useful for short-term forecasting of inflation. There is no serious evidence of a link between mobile money and inflation.

Suggested Citation

  • Muellbauer, John & Aron, Janine & Sebudde, Rachel, 2015. "Inflation forecasting models for Uganda: is mobile money relevant?," CEPR Discussion Papers 10739, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:10739
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    2. Ochen, Ronald & Bulime, Enock Will Nsubuga, 2023. "Digital Financial Services regulations: Their evolution and impact on financial inclusion in East Africa," KBA Centre for Research on Financial Markets and Policy Working Paper Series 73, Kenya Bankers Association (KBA).
    3. Olukorede Abiona & Martin Foureaux Koppensteiner, 2022. "Financial Inclusion, Shocks, and Poverty: Evidence from the Expansion of Mobile Money in Tanzania," Journal of Human Resources, University of Wisconsin Press, vol. 57(2), pages 435-464.
    4. Qiu, Christina M., 2022. "Regionalized liquidity: A cross-country analysis of mobile money deployment and inflation in developing economies," World Development, Elsevier, vol. 152(C).
    5. Ablam Estel Apeti & Jean-Louis Combes & Eyah Denise Edoh, 2023. "Entrepreneurship in developing countries: can mobile money play a role?," Working Papers hal-04081304, HAL.
    6. Apeti, Ablam Estel & Edoh, Eyah Denise, 2023. "Tax revenue and mobile money in developing countries," Journal of Development Economics, Elsevier, vol. 161(C).
    7. Godfred Anakpo & Zizipho Xhate & Syden Mishi, 2023. "The Policies, Practices, and Challenges of Digital Financial Inclusion for Sustainable Development: The Case of the Developing Economy," FinTech, MDPI, vol. 2(2), pages 1-17, June.
    8. Joseph Mawejje & Paul Lakuma, 2019. "Macroeconomic effects of Mobile money: evidence from Uganda," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-20, December.
    9. Samuel Orekoya, Phd, . "Impact Of Mobile Money On Prices And Output In Nigeria," Journal of Economic and Sustainable Growth 1, Office Of The Chief Economist, Development Bank of Nigeria.
    10. Aron, Janine, "undated". "'Leapfrogging': a Survey of the Nature and Economic Implications of Mobile Money," INET Oxford Working Papers 2017-02, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, revised Jan 2017.
    11. Dorothy Nampewo & Grace Ainomugisha Tinyinondi & Duncan Roy Kawooya & George Wilson Ssonko, 2016. "Determinants of private sector credit in Uganda: the role of mobile money," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-16, December.

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    More about this item

    Keywords

    Error correction models; Mobile money; Model selection; Modelling inflation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • 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
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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