The relationship between the monetary policy cycle and the financial cycle and business cycles in Iran

Abstract
The aim of this study is to analyze the dynamic structure of the contagion of fluctuations between business, monetary and financial cycles in the Iranian economy during the seasonal period of 2011-2024. In this regard, using the time-varying vector autoregression model (TVP-VAR) within the framework of total connectivity indices (TCI), pairwise connectivity (PCI), and net directional connectivity (NPDC), the relationships among the variables of gross domestic product, monetary conditions index, capital market, coin market, housing market and credit-to-output ratio were examined. All the variables were extracted cyclically and through the Hedrick-Prescott filter. The results show that the total connectivity index (TCI) reached higher levels in recessionary and unstable periods and, especially in 2014, 2018 and 2020, the economic structure of Iran suffered from severe co-contagion and end contagion. A PCI analysis indicates that negative shocks are more effective in creating coordination among markets, while positive shocks have had a weaker effect. Also, the results of the Net Directional Connectivity Index (NPDC) show that variables such as the money and capital markets are the net transmitters of shocks in the economic network, and real variables such as GDP and CG have played more of a receiver role. The findings indicate that the Iranian economy is a fragile structure, reactive to negative risks, and has strong internal linkages among its macro components. This structure requires policy-makers to intervene to strengthen resilience, contain negative contagion channels, and design targeted credit and monetary policies. Overall, the present study provides a comprehensive picture of the contagion mechanism in the Iranian economy and emphasizes the need to adopt structural countercyclical policies.
Extended Abstract
Purpose: The primary objective of this research is to analyze the dynamic structure of spillovers and interconnections among business cycles, monetary policy cycles, and financial cycles in the Iranian economy over the quarterly period of 2011-2024. This study addresses a critical gap in the macroeconomic literature by examining the time-varying and asymmetric relationships among these cycles, particularly in an emerging economy characterized by structural vulnerabilities such as international sanctions, chronic inflation, currency instability, and heavy reliance on oil revenues. Traditional views in neoclassical and monetarist schools posit that monetary policy cycles and financial cycles operate independently of business cycles, with monetary policy primarily focused on inflation control and output stabilization. In the Iranian context, the Central Bank's efforts to maintain stability via inflation targeting and expansionary or contractionary monetary policies have been challenged by frequent disruptions in financial markets (e.g., housing, stocks, and gold) and real sector fluctuations. By focusing on time-varying parameters and directional spillovers, the study seeks to inform more effective policy design, enhance resilience against negative shocks, and promote counter-cyclical interventions. Ultimately, it provides a comprehensive mapping of spillover mechanisms, highlighting the need for integrated monetary and macro prudential policies in fragile economies like Iran's.

Methodology: This study adopts a rigorous econometric approach to capture the dynamic and time-varying nature of spillovers. The key variables include the quarterly cycles extracted from real GDP growth (business cycle), the Monetary Conditions Index (MCI, monetary cycle, derived from credit volume, exchange rate, and inflation using a Vector Auto regression model, stock market returns (TI), real gold prices (CO), real housing prices (HO), and the credit-to-GDP ratio (CG, financial cycles). To isolate the cyclical components, all the series are de-trended using the Hodrick-Prescott (HP) filter with a λ value of 1600 for quarterly data, ensuring robustness through sensitivity tests with the λ values of 1000 and 2200.
The core methodology is the Time-Varying Parameter Vector Auto regression (TVP-VAR) model, extended with Bayesian estimation and Kalman filtering to estimate the evolving coefficients and variance-covariance matrices, as formalized in Equations (3) and (4). This overcomes the limitations of static VAR or rolling-window approaches by endogenously capturing structural breaks without arbitrary window lengths. Spillover indices are derived from Generalized Forecast Error Variance Decomposition (GFEVD), following Diebold and Yilmaz (2009, 2012, 2014) and Primiceri (2005), scaled per Koop et al. (1996) and Pesaran and Shin (1998). The Total Connectedness Index (TCI) measures the overall network integration (Equation 10, normalized to 0-1 per Chatziantoniou and Gabauer, 2021). The Net Pairwise Directional Connectedness (NPDC) assesses net directional spillovers between pairs (Equations 7-9). Also, the Pairwise Connectedness Index (PCI) quantifies bilateral spillovers (Equation 12, decomposed from TCI per Equation 13).
Business cycle phases are identified using the Bry-Boschan-Quarterly (BBQ) algorithm adapted by Harding and Pagan (2002) for turning points. Descriptive statistics, unit root tests (ERS), normality (Jarque-Bera), autocorrelation (Q and Q²), and Pearson correlations validate the data. The TVP-VAR framework allows for the asymmetric analysis of positive (green line) and negative (red line) shocks, with black shaded areas indicating TCI bounds.

Findings and Discussion: Empirical results reveal a highly interconnected and fragile economic structure in Iran, prone to amplified spillovers during recessions. The TCI exhibits peaks above 55% in 2014, 2018, and 2020, coinciding with sanctions, currency shocks, and COVID-19 disruptions. This indicates intensified systemic co-movements (Figure 2). Overall, TCI stabilizes at 45% post-2020, suggesting persistent endogenous spillovers even absent external shocks. An asymmetric analysis underscores negative shocks' dominance; red lines consistently exceed green lines, implying greater contagion from downturns (e.g., GDP contractions or asset price drops) than expansions, reflecting structural risk aversion and institutional weaknesses. PCI pairwise indices highlight episodic co-movements; GDP drives early synchrony (60% with MCI/TI in 2011-2016), but it fades post-2017 amid real sector lags. CG exhibits robust links with HO and MCI (2013-2017), amplifying credit booms, while TI and CO show crisis-driven spikes (2018-2020). Negative shocks prevail in most pairs (e.g., GDP-MCI, TI-HO), except CG where positives dominate. This indicates credit's counter-cyclical potential. BBQ phase detection confirms five GDP cycles (average recession: five quarters), with financial cycles shorter and more volatile (TI: < 4 quarters), and gold's counter-cyclical refuge behavior during recessions (2019-2020).
These findings align with Antonakakis et al. (2020, 2023) on dynamic connectedness in volatile economies, but they reveal Iran's unique asymmetry. Indeed, financial sub-cycles (especially safe-haven assets) dominate real spillovers, exacerbating fragility. Unlike developed economies, positive shocks yield weak propagation, signaling low confidence and incomplete transmission channels. The structural brittleness, evident in slow real responses to financial cues, amplifies negative risks, consistent with the study by Borio (2012) on financial cycle depth.

Conclusions and Policy Implications: In conclusion, the Iranian economy has a brittle, inwardly connected structure where monetary, financial, and business cycles exhibit strong, time-varying spillovers, disproportionately driven by negative shocks. TVP-VAR estimates confirm high TCI persistence, with financial transmitters (CO, TI) overwhelming real receivers (GDP, CG), and MCI as a pivotal conduit. This asymmetry underscores vulnerability to downturns, limiting positive shock efficacy and perpetuating instability amid sanctions and oil dependence. The study advances the literature by pioneering TVP-VAR connectedness in Iran's context, revealing sub-cycle nuances absent in prior static analyses.
The policy implications of this study are profound. To bolster resilience, authorities must prioritize counter-cyclical macro prudential tools, such as dynamic reserve requirements and credit quotas to curb asset bubbles (e.g., cap CG growth during TI/HO booms, as in 2014-2017). Broader reforms include high-frequency monitoring for preemptive action and anti-speculative measures (e.g., capital gains taxes on TI/CO). These align with Juselius et al. (2016) and Richter et al. (2019), advocating lean-against-the-wind policies. By addressing endogenous spillovers, Iran can transition from reactive to proactive frameworks, promoting sustainable growth and welfare in a sanction-prone environment.