https://ijes.shirazu.ac.ir/ Iranian Journal of Economic Studies en daily 1 Mon, 01 Jun 2026 00:00:00 +0330 Mon, 01 Jun 2026 00:00:00 +0330 https://ijes.shirazu.ac.ir/article_8589.html Accurate forecasts of the mega-cap technology stocks—Apple, Amazon, Alphabet, Meta and Microsoft—are vital for risk management and asset allocation. This study proposes a stacking ensemble that fuses Support Vector Regression (SVR), Random Forests (RF) and Extreme Gradient Boosting (XGBoost) as base learners, with a parsimonious linear meta-learner. We use daily OHLC data from 2 January 2020 to 11 March 2025, a span capturing the volatility of the COVID-19 shock and its aftermath. After differencing to ensure stationarity, the target variable becomes the daily change in closing price (Δ"Close" ). Models are trained on an expanding 80% window and tested on the final 20% of observations. Performance is assessed on strictly out-of-sample predictions using RMSE, MAE, MSE, and R^2. Across all five firms, the ensemble achieves the highest explanatory power (R^2≈0.80"-" 0.83) for predicting daily price changes and lowers RMSE by 8–15% relative to the best individual model. Friedman tests show these improvements are significant at the 1% level for Microsoft, Meta and Alphabet, and at 5% for Amazon; Apple shows no significant difference. The results indicate that combining heterogeneous learners curbs overfitting and exploits complementary nonlinear and temporal signals, producing stable forecasts during extreme market stress. The framework provides investors and policymakers with a validated AI tool for improving risk-return profiles in tech-heavy portfolios and offers methodological guidance for future financial-forecasting research. https://ijes.shirazu.ac.ir/article_8628.html Based on empirical evidence backed by quantity theory of money, there is a proportionate reaction of the price level to an exogenous increase in the nominal money stock and it can cause a persistent inflation. However, governments control the relation between liquidity growth and inflation in the short run by managing exchange rate. Inflation control through government intervention using exchange rate in Iran, as an oil exporting country took place in last decades. Bearing sanctions in mind, exchange rate had significant overshoots causing two states in Iranian monetary environment. To capture the dynamics, this study using TAR estimation for liquidity, exchange rate and price levels over the period 2001-2025, detected exchange rate growth as the threshold variable at the value of 11% dividing economy into two states. In the low exchange rate regime, exchange rate changes have no statistically significant effect on inflation, while liquidity growth emerges as the primary driver and inflation persistence remains strong through significant lagged effects. In contrast, once the threshold is exceeded, exchange rate depreciation becomes a key and highly significant determinant of inflation, indicating intensified pass-through effects under higher volatility. Although liquidity continues to exert a positive and stronger influence, inflation persistence weakens, suggesting a shift from backward-looking dynamics toward contemporaneous shocks and potentially forward-looking expectations. Liquidity with a larger coefficient than in the lower regime, suggesting that monetary expansion has an even stronger inflationary impact under high exchange rate volatility which could not be suppressed. https://ijes.shirazu.ac.ir/article_8632.html This study investigates the multidimensional spatial patterns characterizing the relationship between financial stress and financial market growth among companies listed on the Tehran Stock Exchange. The research incorporates three critical dimensions: spatial interdependencies, network structures, and inter-sectoral interactions. The analytical framework employs the innovative Multidimensional Spatial Panel Autoregressive Hybrid Model (MSPAHM), which facilitates simultaneous examination of temporal dynamics, spatial dependencies, and sectoral heterogeneity across the economic landscape. The empirical analysis encompasses a comprehensive dataset of Tehran Stock Exchange-listed companies spanning 2010 to 2024, capturing multiple economic cycles and policy regimes. The findings reveal that financial stress exerts a significant negative impact on firms' financial growth, with effects propagating through spatial spillover mechanisms to interconnected companies within the broader economic network. This transmission occurs across both direct and indirect channels, creating cascading effects throughout the market structure. Notably, the analysis identifies substantial sectoral variation in vulnerability patterns. Capital-intensive and import-dependent industries demonstrate heightened susceptibility to financial stress shocks, with effect magnitudes intensifying markedly during periods of economic sanctions and maximum pressure policies. These results underscore the dynamic and networked nature of financial stress, emphasizing its dependence on sectoral characteristics and temporal contexts. The study concludes that effective policy intervention requires adopting a systemic approach grounded in comprehensive network analysis, enabling policymakers to anticipate spillover effects and design targeted interventions that account for the interconnected nature of firm-level financial distress within the broader economic ecosystem. https://ijes.shirazu.ac.ir/article_8640.html This study identifies a theoretical puzzle: while agency theory predicts that all forms of uncertainty increase accounting conservatism as a precautionary buffer, we find that market turbulence reduces it. This paradoxical reversal cannot be explained by standard risk-aversion frameworks. Using a balanced panel of 154 firms listed on the Tehran Stock Exchange over 2015-2024 (1,540 firm-year observations), we employ FGLS as our primary estimator, complemented by System GMM to address endogeneity. Our findings reveal a fundamental asymmetry consistent with our proposed Conditional Dominance Framework: market risk has a positive and significant effect on conservatism, supporting the agency-theoretic view of conservatism as a rational response to mitigate agency costs. Conversely, market turbulence exerts a negative and significant impact, consistent with Prospect Theory's prediction that under ambiguity and loss-domain conditions, managers become risk-seeking and abandon prudent reporting. Critically, this behavioral reversal is not constant but is activated and amplified by adverse macroeconomic conditions—inflation and exchange rate depreciation—which act as cognitive regime-switches. Economic growth and higher real interest rates weaken these relationships. The primary contribution is demonstrating that financial reporting conservatism is not merely a strategic response but a fragile defense mechanism that systematically collapses under extreme macro-volatility, challenging the implicit assumption that conservatism always increases with uncertainty. Our findings offer critical insights for managers, investors, and policymakers navigating volatile emerging economies.  https://ijes.shirazu.ac.ir/article_8649.html This study employs a calibrated Dynamic Stochastic General Equilibrium (DSGE) model to compare endogenous liquidity creation and its allocation in Iran, Armenia, and Azerbaijan over 2005–2024. It significantly contributes by introducing a structural Liquidity Distribution Indicator (LDI), measuring the share of bank-created liquidity allocated to firm lending. Countries are selected based on similar Liquidity Creation Intensity (LCI), defined as the ratio of central bank borrowing to total deposits. The model features a representative household and bank with financial frictions to analyze how balance sheet liquidity allocation affects the transmission of a –1% lending rate shock, interpreted as a relaxation of credit conditions before and after COVID-19. Calibrated to country-specific financial structures and solved using a fully nonlinear routine, the model generates impulse responses from nonlinear transition dynamics. Results show that before COVID-19, banks in Iran and Armenia allocated a relatively small share of liquidity to firm lending, with Azerbaijan displaying a similar pattern driven by state-dominated intermediation. Although post-COVID liquidity support temporarily increased lending shares, structural banking features continued to constrain effective monetary transmission. Overall, interest rate policy alone appears insufficient to mitigate risks from concentrated liquidity allocation; strengthening credit allocation mechanisms and banking intermediation is essential for macro-financial stability. https://ijes.shirazu.ac.ir/article_8694.html This study examines the asymmetric and nonlinear effects of exchange rate fluctuations on Iran’s stock market index and industrial production over the period 2009–2024, with the explicit aim of quantifying the differential sensitivity of financial and real sectors to currency depreciation and appreciation shocks under varying macroeconomic regimes. A hybrid analytical framework is employed, integrating the Nonlinear Autoregressive Distributed Lag (NARDL) model for asymmetric cointegration analysis, a Hidden Markov Model (HMM) for endogenous regime identification, Gaussian Process Regression (GPR) for Bayesian uncertainty quantification, and a Transformer architecture for temporal attention-based forecasting. Monthly data spanning 2009–2024 are utilized, with all variables confirmed as through ADF, PP, and KPSS unit root tests. Bounds testing confirms stable long-run cointegrating relationships in both models ( and , respectively). Long-run asymmetry is significant in both sectors; negative shocks exert effects approximately times larger than positive shocks in the stock market ( vs. ) and times larger in industrial production ( vs. ). The HMM identifies two structurally distinct regimes — stable and turbulent — wherein turbulent-regime coefficients exceed stable-regime estimates by a factor exceeding two. The hybrid framework achieves RMSE reductions of 38% and 24% over benchmark models for the stock market and industrial production, respectively. Exchange rate shocks in Iran operate through asymmetric, regime-dependent, and nonlinear channels, with financial markets exhibiting substantially greater sensitivity than the real sector. Symmetric currency management policies are structurally inadequate; preemptive, regime-sensitive intervention instruments are required. https://ijes.shirazu.ac.ir/article_8696.html This study employs spatial econometric methods to examine the impact of gas consumption on electricity consumption across Iranian provinces from 2006 to 2019. Key variables analyzed include gas consumption, gross domestic product, urban population, average temperature, and average electricity prices. The results indicate that provincial income, population, total gas consumption, and degree of industrialization positively influence electricity consumption, with industrialized provinces exhibiting higher electricity demand. Furthermore, total gas consumption significantly increases electricity consumption, reflecting the essential role of gas in electricity generation. The positive and significant spatial lag coefficient of electricity consumption highlights the importance of spatial dependence, suggesting that increases in electricity consumption in one province lead to corresponding increases in neighboring provinces. Overall, the findings confirm the significant effect of gas consumption on electricity demand while emphasizing spatial spillover effects among provinces. https://ijes.shirazu.ac.ir/article_8698.html This study investigates the nonlinear, state-dependent dynamics of exchange rate pass-through (ERPT) across Producer Price Index (PPI) sub-sectors in Iran, utilizing quarterly time-series data spanning from 2000Q2 to 2025Q4. Employing a threshold regression framework to capture asymmetric price transmission under varying macroeconomic conditions, the analysis distinguishes between low- and high-inflation expectations regimes. Empirical findings reveal a pronounced regime-dependent escalation in ERPT; at the aggregate level, pass-through elasticity surges from 0.525 in the low-inflation regime to 0.730 in the high-inflation regime, underscoring the pivotal role of inflation expectations in amplifying the transmission of exchange rate shocks into producer prices. This pattern persists robustly across more than two decades of structural economic evolution. Sectoral heterogeneity is particularly evident, with manufacturing and agriculture exhibiting the most significant increases (from 0.607 to 0.938 and 0.467 to 0.868, respectively), reflecting their enduring reliance on imported intermediate inputs. Similarly, the mining and oil & gas sectors demonstrate marked regime shifts consistent with nonlinear adjustment mechanisms in resource-based production. Collectively, these results confirm that ERPT in the Iranian economy is fundamentally nonlinear and state-dependent, with inflation expectations serving as a critical amplification channel. Consequently, the study emphasizes the necessity of accounting for regime shifts, long-run structural transformations, and seasonal dynamics to accurately model exchange rate transmission to producer prices.