Skip to main content

Advertisement

SpringerLink
Log in

An overview of causal factors in fluctuations of some economic indices in Iran using impulse response analysis (1990–2022)

  • Original Article
  • Published:
Modeling Earth Systems and Environment Aims and scope Submit manuscript

Abstract

In recent decades, the Iranian economy has experienced unprecedented financial challenges, resulting in fluctuations in some economic indices. In this study, the impulse response analysis was conducted to identify the causal factors, which are responsible for fluctuating two main indices of gold and land prices during 1990–2022. For this purpose, a vector autoregression model (VAR), with 12 endogenous variables, was constructed, using EViews software. The results revealed that the shock of the inflation rate, market capitalization, and gasoline prices will not significantly fluctuate gold and land prices in Iran. Besides, the results revealed that some variables, such as GDP per capita, stock traded value, the exchange rate, global gold price, and global oil price may fluctuate national gold and land indices in Iran during the observation periods. Among these causal factors, only the shock of exchange rate, with high decomposition variance (> 78%), will immediately fluctuate national gold and land prices. Hence, the co-movement of gold and land price toward the signals of the exchange rate is obvious and could be forecasted for future periods. An important managerial implication is to focus on the controlling approaches of the exchange rate, which is the main driving power of economic fluctuations and instabilities in Iran.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author upon request.

Abbreviations

ADF:

Augmented Dickey Fuller

CO2:

CO2 Emissions

EXC:

Exchange Rate

FMI:

Financial Development Index

JCOPA:

Joint Comprehensive Plan of Action

GSL:

Gasoline Price

GGLD:

Global Gold Price

GOIL:

Global Oil Price

GDP:

Gross Domestic Product

INF:

Inflation Rate

IRR [Reference currency]:

Iranian Rial

10-IRR [Public currency]:

Iranian Toman

Mt:

Million tons

NGLD:

National Gold Price

MRK:

Market Capitalization

LND:

Mean Land Price

INC:

Minimum Income

STC:

Stock Treaded

SC:

Schwarz Information Criterion

S.D.:

Standard Deviation

S.E.:

Standard Error

U.N.:

United Nations

U.S.:

United States

USD:

United States Dollar

VAR:

Vector Autoregression Model

References

  • Akbar M, Iqbal F, Noor F (2019) Bayesian analysis of dynamic linkages among gold price, stock prices, exchange rate and interest rate in Pakistan. Resour Policy 62(4):154–164

    Article  Google Scholar 

  • Asaad ZA (2021) Oil price, gold price, exchange rate and stock market in Iraq pre-during COVID19 outbreak: an ARDL approach. Int J Energy Econ Policy 11(5):562–571

    Article  Google Scholar 

  • Atamanov A, Mostafavi MH, Salehi-Isfahani D, Vishwanath T (2016) Constructing Robust Poverty Trends in the Islamic Republic of Iran, 2008-14. Policy Research Working Paper, No. 7836. World Bank, Washington, DC. https://openknowledge.worldbank.org/handle/10986/25152

  • Baur DG, Lucey BM (2010) Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financ Rev 45(2):217–229

    Article  Google Scholar 

  • Berument MH, Denaux Z, Yalcin Y (2012) Turkish Monetary Policy and Components of Aggregate demand: a VAR analysis with sign restrictions Model. Appl Econ 44:4787–4798

    Article  Google Scholar 

  • Brown P (2020) Oil Market effects from U.S. Economic sanctions: Iran, Russia, Venezuela. Congressional Res Service 7:R46213

    Google Scholar 

  • Cheng Q, Jiao J, Chen H, Xu F (2019) Application of impulse response method in identifying the causes of gold price fluctuation. Ingenierie Des Systemes d’Information 24:61–66

    Google Scholar 

  • Dabla-Norris E, Srivisal N (2013) Revisiting the link between finance and macroeconomic volatility. IMF Working Paper 13/29. International Monetary Fund, Washington

  • Daneshvar MR, Abadi NH (2017) Spatial and temporal variation of nitrogen dioxide measurement in the Middle East within 2005–2014. Model Earth Syst Environ 3:20

    Article  Google Scholar 

  • Dedola L, Neri S (2007) What does a technology shock do? A VAR analysis with model-based sign restrictions. J Monet Econ 54(2):512–549

    Article  Google Scholar 

  • Demirgüç-Kunt A, Levine R (2009) Finance and Inequality: theory and evidence. Annual Rev Financial Econ 1(1):287–318

    Article  Google Scholar 

  • Dinh DV (2020) Impulse response of inflation to economic growth dynamics: VAR model analysis. J Asian Finance Econ Bus 7(9):219–228

    Article  Google Scholar 

  • Djurovic G, Djurovic V, Bojaj MM (2020) The macroeconomic effects of COVID-19 in Montenegro: a bayesian VARX approach. Financ Innov 6:40

    Article  Google Scholar 

  • Fanack (2022) Economy of Iran, archived by chronicle of the Middle East and North Africa. https://fanack.com/iran/economy-of-iran. Accessed 2022.

  • Farrant K, Peersman G (2006) Is the Exchange Rate a shock absorber or a source of shocks? New empirical evidence. J Money Credit Bank 38(4):939–961

    Article  Google Scholar 

  • Guo J, Zhang L, Guo R (2023) Relative humidity prediction with covariates and error correction based on SARIMA-EG-ECM model. Model Earth Syst Environ. https://doi.org/10.1007/s40808-023-01738-x

    Article  Google Scholar 

  • IMF (2022) Financial development index database, archived by International Monetary Fund. https://www.imf.org/en/Home. Accessed 2022

  • Karimuzzaman M, Hossain MM (2020) Forecasting performance of nonlinear time-series models: an application to weather variable. Model Earth Syst Environ 6:2451–2463

    Article  Google Scholar 

  • Kazemi MN, Takeuchi R, Kiku L (2020) Iran Economic Monitor: Weathering the Triple-Shock (English). Washington, D.C. World Bank Group. http://documents.worldbank.org/curated/en/287811608721990695

  • Kelishomi AM, Nisticò R (2021) Employment Effects of Economic Sanctions in Iran, IZA Discussion Papers, No. 14814, Institute of Labor Economics (IZA), Bonn

  • Khan I, Khan N, Yaqub A, Sabir M (2019) An empirical investigation of the determinants of CO2 emissions: evidence from Pakistan. Environ Sci Pollut Res 26(9):9099–9112

    Article  CAS  Google Scholar 

  • Kilian L, Murphy D (2013) The role of inventories and speculative trading in the Global Market for Crude Oil. J Appl Econom 29:454–478

    Article  Google Scholar 

  • Levine R (2005) Finance and growth: theory and evidence. In: Aghion P, Durlauf S (Ed.), Handbook of Economic Growth, 12:865–934

  • Lewis VJ (2007) Productivity and the Euro–Dollar Real Exchange Rate. Rev World Econ 143(2):324–348

    Article  Google Scholar 

  • Lu Y (2019) Empirical analysis on the influential factors of real Estate price: a panel VAR model view. Adv Econ Bus Manage Res 96:232–238

    Google Scholar 

  • Maboudian E, Ehsani MA (2020) The Effect of Key macroeconomic shock variables on GDP in Iran: a sign-restricted bayesian VAR Approach. Iran. Econ Rev 24(4):1099–1118

    Google Scholar 

  • Mamipour S, Yahoo M, Jalalvandi S (2019) An empirical analysis of the relationship between the environment, economy, and society: results of a PCA-VAR model for Iran. Ecol Ind 102:760–769

    Article  Google Scholar 

  • Monfared SS, Akın F (2017) The relationship between exchange rates and inflation: the case of Iran. Eur J Sustainable Dev 6(4):329–340

    Article  Google Scholar 

  • Najafabadi AM, Qazvini M, Ofoghi R (2012) The impact of oil and gold prices’ shock on Tehran Stock Exchange: a Copula Approach. Iran J Economic Stud 1(2):23–47

    Google Scholar 

  • Nawaz F, Hassan SA (2023) Hydroclimatic modelling of upper Indus basin rivers predictability. Model Earth Syst Environ. https://doi.org/10.1007/s40808-023-01785-4

    Article  Google Scholar 

  • Ouliaris S, Pagan AR, Restrepo J (2018) Quantitative Macroeconomic Modeling with Structural Vector Autoregressions - An EViews Implementation. Institute for Capacity Development. https://www.eviews.com/StructVAR/structvar.html. Accessed 2022

  • Peersman G, Straub R (2009) Technology shocks and Robust sign restrictions in a Euro Area SVAR. Int Econ Rev 50(3):727–750

    Article  Google Scholar 

  • Sadorsky P (2014) Modeling volatility and correlations between emerging market stock prices and the prices of copper, oil and wheat. Energy Econ 43:72–81

    Article  Google Scholar 

  • Samadi AH, Owjimehr S, Halafi ZN (2021) The cross-impact between financial markets, Covid-19 pandemic, and economic sanctions: the case of Iran. J Policy Model 43:34–55

    Article  Google Scholar 

  • SCI (2022) Macro results of statistical survey, archived by Statistical Center of Iran. https://www.amar.org.ir/statistical-information. Accessed 2022

  • Shabbir A, Kousar S, Batool SA (2020) Impact of gold and oil prices on the stock market in Pakistan. J Econ Finance Administrative Sci 25(50):279–294

    Article  Google Scholar 

  • Shafiee S, Topal E (2010) An overview of global gold market and gold price forecasting. Resour Policy 35:178–189

    Article  Google Scholar 

  • Sims CA (1980) Macroeconomics and reality. Econometrica: Journal of the Econometric Society, 48: 1–48

  • Tavakoli A, Shafie-Pour M, Ashrafi K, Abdoli G (2016) Options for sustainable development planning based on GHGs emissions reduction allocation (GERA) from a national perspective. Environ Dev Sustain 18(1):19–35

    Article  Google Scholar 

  • Torki L, Samadi S, Safrpoor Z (2021) Analysis of the effect of macroeconomic variables on fluctuation of Future Gold Market in Iran. Int J Econ Politics 2(1):251–272

    Article  Google Scholar 

  • UNDP (2022) Human development index, archived by United Nations Development Programme. https://hdr.undp.org/data-center/human-development-index. Accessed 2022.

  • World Bank (2022) World development indicators, archived by online public web resource of World data bank, Washington. https://databank.worldbank.org/source/world-development-indicators. Accessed 2022

  • World Bank Group (2016) Iran Economic Monitor, fall 2016: towards reintegration. Iran Economic Monitor. World Bank, Washington, DC. https://openknowledge.worldbank.org/https://handle.net/10986/25865

    Book  Google Scholar 

  • World Bank Group (2022) Iran Economic Monitor, Spring 2022: managing Economic uncertainties. Iran Economic Monitor. World Bank, Washington, DC. https://openknowledge.worldbank.org/https://handle.net/10986/37792

    Book  Google Scholar 

Download references

Acknowledgements

We thank anonymous reviewers for technical suggestions on data interpretations.

Funding

This study was not funded by any grant.

Author information

Authors and Affiliations

  1. Department of Geography and Natural Hazards, Research Institute SP, Mashhad, Iran

    Mohammad Reza Mansouri Daneshvar

  2. Department of Accounting, Shafagh University of Tonekabon, Mazandaran, Iran

    Ali Sohrabi

  3. Department of Humanities and Social Science, Farhangian University, Tehran, Iran

    Ali Sadeghi

  4. Department of Urban Planning and Design, Islamic Azad University, Mashhad, Iran

    Rayeheh Khatami

Authors
  1. Mohammad Reza Mansouri Daneshvar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ali Sohrabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ali Sadeghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rayeheh Khatami
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors were equally involved in data analyzing, defining the strategies, and editing the paper. Also, all authors read and approved the final manuscript.

Corresponding author

Correspondence to Mohammad Reza Mansouri Daneshvar.

Ethics declarations

Classification

Economics.

Statistical Analysis.

Competing interests

The authors declare that they have no Competing interests.

Ethics approval and consent to participate

This article does not contain any studies with participants performed by any of the authors.

Informed consent

Informed consent was obtained from individual participant included in the study.

Consent for publication

Not applicable.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mansouri Daneshvar, M.R., Sohrabi, A., Sadeghi, A. et al. An overview of causal factors in fluctuations of some economic indices in Iran using impulse response analysis (1990–2022). Model. Earth Syst. Environ. 10, 1959–1971 (2024). https://doi.org/10.1007/s40808-023-01886-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40808-023-01886-0

Keywords

Search

Navigation