Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka

Rohini Dunuwita Liyanage

doi:doi:10.11648/j.ijebo.20231102.13

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Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka

Rohini Dunuwita Liyanage

Published in International Journal of Economic Behavior and Organization (Volume 11, Issue 2)

Received: 11 April 2023 Accepted: 10 May 2023 Published: 24 May 2023

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Abstract

Elevated inflation again has been a key macroeconomic problem that impacts negatively on economic activities in recent times. Inflation is widely used as a short run monetary policy tool that has impact on redistribution of resources through price transmission mechanism in economies. Forecasting is also a challenging task with high volatilities of the price index that use to measure inflation. However, inflation forecasts are essential in setting monetary policy targets and the decision-making process in the short run. In Sri Lanka inflation recorded at its highest level ever in the year 2022 reversing its single digit inflation maintained in a decade. The aim of this paper is to estimate an inflation forecasting model using Automatic ARIMA technique in Sri Lanka employing data from 2014M01 to 2023M01 towards forecasting end point to end 2024, using secondary sourced monthly data. Accordingly, Colombo Consumer Price Index shows a further upward trend forecasting range given in CCPIC index point from 224 to 260 during the period for inflation measured using year on year base is in declining trend, below 10 per cent, but not par equal to the mid-single level as per the data, CCPI 2013=100. Given the demand full inflation factors, policies to encourage supply and production are recommended in the medium term.

Published in	International Journal of Economic Behavior and Organization (Volume 11, Issue 2)
DOI	10.11648/j.ijebo.20231102.13
Page(s)	49-60
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Inflation, Forecasting, Automatic ARIMA, Sri Lanka

References

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[4]	Hussain, Shahzad, and Shahnawaz Malik. "Inflation and Economic Growth: Evidence From Pakistan." International Journal of Economics and Finance 3.5 (2011): 262-76. Print.
[5]	Aslam, AL, and SM Lebbe. "Inflation and Economic Growth In Sri Lanka: An Ardl Bound Testing Approach." (2017). Print.
[6]	Madurapperuma, Wasanthi. "Impact of Inflation on Economic Growth in Sri Lanka." Journal of World Economic Research 5.1 (2016): 1-7. Print.
[7]	Liyanage, Rohini Dunuwita. "Impact of Inflation on Labour Productivity In Sri Lanka." Organization 9.3 (2021): 57-70. Print.
[8]	Groen, Jan JJ, Richard Paap, And Francesco Ravazzolo. "Real-Time Inflation Forecasting in a Changing World." Journal of Business & Economic Statistics 31.1 (2013): 29-44. Print.
[9]	Atkeson, Andrew, and Lee E Ohanian. "Are Phillips Curves Useful For Forecasting Inflation?" Federal Reserve Bank Of Minneapolis Quarterly Review 25.1 (2001): 2-11. Print.
[10]	Stock, James H, and Mark W Watson. "Forecasting Inflation." Journal of Monetary Economics 44.2 (1999): 293-335. Print.
[11]	ÖğÜNç, Fethi, et al. "Short-Term Inflation Forecasting Models for Turkey and A Forecast Combination Analysis." Economic Modelling 33 (2013): 312-25. Print.
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[13]	Jesmy, ARS. "Estimation of Future Inflation In Sri Lanka Using Arima Model." (2012). Print.
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[17]	Uko, AHAM KELVIN, and Emeka Nkoro. "Inflation forecasts with ARIMA, vector autoregressive and error correction models in Nigeria." European Journal of Economics, Finance & Administrative Science 50 (2012): 71-87.
[18]	Meyler, Aidan, Geoff Kenny, And Terry Quinn. "Forecasting Irish Inflation Using Arima Models." (1998). Print.

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APA Style

Rohini Dunuwita Liyanage. (2023). Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka. International Journal of Economic Behavior and Organization, 11(2), 49-60. https://doi.org/10.11648/j.ijebo.20231102.13

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ACS Style

Rohini Dunuwita Liyanage. Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka. Int. J. Econ. Behav. Organ. 2023, 11(2), 49-60. doi: 10.11648/j.ijebo.20231102.13

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AMA Style

Rohini Dunuwita Liyanage. Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka. Int J Econ Behav Organ. 2023;11(2):49-60. doi: 10.11648/j.ijebo.20231102.13

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@article{10.11648/j.ijebo.20231102.13,
  author = {Rohini Dunuwita Liyanage},
  title = {Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka},
  journal = {International Journal of Economic Behavior and Organization},
  volume = {11},
  number = {2},
  pages = {49-60},
  doi = {10.11648/j.ijebo.20231102.13},
  url = {https://doi.org/10.11648/j.ijebo.20231102.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijebo.20231102.13},
  abstract = {Elevated inflation again has been a key macroeconomic problem that impacts negatively on economic activities in recent times. Inflation is widely used as a short run monetary policy tool that has impact on redistribution of resources through price transmission mechanism in economies. Forecasting is also a challenging task with high volatilities of the price index that use to measure inflation. However, inflation forecasts are essential in setting monetary policy targets and the decision-making process in the short run. In Sri Lanka inflation recorded at its highest level ever in the year 2022 reversing its single digit inflation maintained in a decade. The aim of this paper is to estimate an inflation forecasting model using Automatic ARIMA technique in Sri Lanka employing data from 2014M01 to 2023M01 towards forecasting end point to end 2024, using secondary sourced monthly data. Accordingly, Colombo Consumer Price Index shows a further upward trend forecasting range given in CCPIC index point from 224 to 260 during the period for inflation measured using year on year base is in declining trend, below 10 per cent, but not par equal to the mid-single level as per the data, CCPI 2013=100. Given the demand full inflation factors, policies to encourage supply and production are recommended in the medium term.},
 year = {2023}
}

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TY  - JOUR
T1  - Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka
AU  - Rohini Dunuwita Liyanage
Y1  - 2023/05/24
PY  - 2023
N1  - https://doi.org/10.11648/j.ijebo.20231102.13
DO  - 10.11648/j.ijebo.20231102.13
T2  - International Journal of Economic Behavior and Organization
JF  - International Journal of Economic Behavior and Organization
JO  - International Journal of Economic Behavior and Organization
SP  - 49
EP  - 60
PB  - Science Publishing Group
SN  - 2328-7616
UR  - https://doi.org/10.11648/j.ijebo.20231102.13
AB  - Elevated inflation again has been a key macroeconomic problem that impacts negatively on economic activities in recent times. Inflation is widely used as a short run monetary policy tool that has impact on redistribution of resources through price transmission mechanism in economies. Forecasting is also a challenging task with high volatilities of the price index that use to measure inflation. However, inflation forecasts are essential in setting monetary policy targets and the decision-making process in the short run. In Sri Lanka inflation recorded at its highest level ever in the year 2022 reversing its single digit inflation maintained in a decade. The aim of this paper is to estimate an inflation forecasting model using Automatic ARIMA technique in Sri Lanka employing data from 2014M01 to 2023M01 towards forecasting end point to end 2024, using secondary sourced monthly data. Accordingly, Colombo Consumer Price Index shows a further upward trend forecasting range given in CCPIC index point from 224 to 260 during the period for inflation measured using year on year base is in declining trend, below 10 per cent, but not par equal to the mid-single level as per the data, CCPI 2013=100. Given the demand full inflation factors, policies to encourage supply and production are recommended in the medium term.
VL  - 11
IS  - 2
ER  -

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Author Information

Rohini Dunuwita Liyanage

Department of Economics, University of Colombo, Colombo, Sri Lanka

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Plain Text BibTeX RIS

APA Style

Rohini Dunuwita Liyanage. (2023). Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka. International Journal of Economic Behavior and Organization, 11(2), 49-60. https://doi.org/10.11648/j.ijebo.20231102.13

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ACS Style

Rohini Dunuwita Liyanage. Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka. Int. J. Econ. Behav. Organ. 2023, 11(2), 49-60. doi: 10.11648/j.ijebo.20231102.13

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AMA Style

Rohini Dunuwita Liyanage. Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka. Int J Econ Behav Organ. 2023;11(2):49-60. doi: 10.11648/j.ijebo.20231102.13

Copy | Download

@article{10.11648/j.ijebo.20231102.13,
  author = {Rohini Dunuwita Liyanage},
  title = {Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka},
  journal = {International Journal of Economic Behavior and Organization},
  volume = {11},
  number = {2},
  pages = {49-60},
  doi = {10.11648/j.ijebo.20231102.13},
  url = {https://doi.org/10.11648/j.ijebo.20231102.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijebo.20231102.13},
  abstract = {Elevated inflation again has been a key macroeconomic problem that impacts negatively on economic activities in recent times. Inflation is widely used as a short run monetary policy tool that has impact on redistribution of resources through price transmission mechanism in economies. Forecasting is also a challenging task with high volatilities of the price index that use to measure inflation. However, inflation forecasts are essential in setting monetary policy targets and the decision-making process in the short run. In Sri Lanka inflation recorded at its highest level ever in the year 2022 reversing its single digit inflation maintained in a decade. The aim of this paper is to estimate an inflation forecasting model using Automatic ARIMA technique in Sri Lanka employing data from 2014M01 to 2023M01 towards forecasting end point to end 2024, using secondary sourced monthly data. Accordingly, Colombo Consumer Price Index shows a further upward trend forecasting range given in CCPIC index point from 224 to 260 during the period for inflation measured using year on year base is in declining trend, below 10 per cent, but not par equal to the mid-single level as per the data, CCPI 2013=100. Given the demand full inflation factors, policies to encourage supply and production are recommended in the medium term.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Inflation Forecasting Using Automatic ARIMA Model in Sri Lanka
AU  - Rohini Dunuwita Liyanage
Y1  - 2023/05/24
PY  - 2023
N1  - https://doi.org/10.11648/j.ijebo.20231102.13
DO  - 10.11648/j.ijebo.20231102.13
T2  - International Journal of Economic Behavior and Organization
JF  - International Journal of Economic Behavior and Organization
JO  - International Journal of Economic Behavior and Organization
SP  - 49
EP  - 60
PB  - Science Publishing Group
SN  - 2328-7616
UR  - https://doi.org/10.11648/j.ijebo.20231102.13
AB  - Elevated inflation again has been a key macroeconomic problem that impacts negatively on economic activities in recent times. Inflation is widely used as a short run monetary policy tool that has impact on redistribution of resources through price transmission mechanism in economies. Forecasting is also a challenging task with high volatilities of the price index that use to measure inflation. However, inflation forecasts are essential in setting monetary policy targets and the decision-making process in the short run. In Sri Lanka inflation recorded at its highest level ever in the year 2022 reversing its single digit inflation maintained in a decade. The aim of this paper is to estimate an inflation forecasting model using Automatic ARIMA technique in Sri Lanka employing data from 2014M01 to 2023M01 towards forecasting end point to end 2024, using secondary sourced monthly data. Accordingly, Colombo Consumer Price Index shows a further upward trend forecasting range given in CCPIC index point from 224 to 260 during the period for inflation measured using year on year base is in declining trend, below 10 per cent, but not par equal to the mid-single level as per the data, CCPI 2013=100. Given the demand full inflation factors, policies to encourage supply and production are recommended in the medium term.
VL  - 11
IS  - 2
ER  -

Copy | Download