Iranian Journal of Economic Research

Abstract The present study addressed the question of why countries exhibit substantial disparities in tax revenue performance, using a comprehensive multilevel meta-analysis of 48 empirical studies (799 effect sizes). After accounting for publication bias and relevant moderator variables, the analysis identified the key determinants of tax revenue performance. The findings indicated that gross domestic product (GDP), international trade, inflation, industrial sector value added, and the lagged value of tax revenue exerted significant positive effects on tax revenues. In contrast, agricultural sector value added and corruption had significant negative effects. Foreign direct investment (FDI), however, did not exhibit a statistically significant relationship with tax revenues. Moreover, how tax revenue is measured—whether including or excluding social security contributions—critically shapes the estimated relationships between these determinants and tax revenue. The analysis also demonstrated that methodological choices (e.g., model specification and estimation techniques), the study period, and control variables (e.g., population size and institutional quality) significantly contributed to the heterogeneity observed across prior empirical findings.

Introduction

The persistent disparities in tax-to-GDP ratios across countries pose a critical challenge for policymakers and economists. Numerous empirical studies have examined the determinants of tax revenue, highlighting factors such as economic size, trade openness, sectoral composition, inflation, and institutional quality. However, their findings remain fragmented and, at times, contradictory. These inconsistencies largely arise from differences in methodological approaches, data sources, model specifications, and contextual moderators. To address this gap, the present study aimed to conduct a comprehensive multilevel meta-analysis to synthesize the existing evidence, identify the core determinants of tax revenue, and explain the sources of heterogeneity in prior empirical findings.

Materials and Methods

Adopting a meta-analysis method, the present study systematically identified and synthesized quantitative evidence from 48 empirical studies, yielding 799 effect sizes. The analysis was centered on a meta-regression framework that models reported effect sizes as a function of their standard errors and a vector of moderator variables. This approach enabled the correction for publication bias and the systematic consideration of methodological and contextual heterogeneity across studies.
The empirical model was specified as follows:
 
where   is the reported effect on tax revenue,  ​ is its standard error,  ​ represents moderators, and   is the error term. A multi-level framework was also employed to address dependencies arising from multiple effects per study.

Results and Discussion

The meta-analysis yielded robust, synthesized findings on the key drivers of tax revenue, with the moderator analysis providing critical contextual insights. Among the positive and significant determinants, GDP (Effect Size = 0.20) emerged as a primary driver, confirming that economic scale plays a central role in revenue generation. This effect was the strongest in panel, static, and fixed/random effects models. International trade (Effect Size = 0.068) also exerted a positive and significant influence, indicating that trade openness enhances revenue performance. The effect was particularly pronounced when tax revenue was measured excluding social security (TRISSC), and it remained consistent in static and fixed/random effects models. Industrial value added (Effect Size = 0.079) demonstrated a stable positive impact, with its influence reinforced in model specifications that controlled for GDP, trade, and corruption. The strongest predictor was lagged tax revenue (Effect Size = 0.528), highlighting strong persistence in revenue collection over time. This effect was consistently observed across nearly all model specifications and definitions.
In contrast, several determinants exhibited negative and significant relationships with tax revenue. Agricultural value added (Effect Size = -0.185) significantly constrained revenue mobilization, suggesting that a larger agricultural share in the economy hampers tax collection capacity. This negative relationship became even stronger in models that controlled for inflation, population, and corruption. Corruption (Effect Size = -0.156) also consistently undermined tax revenue performance, with the effect most pronounced in panel and static models. Foreign direct investment (FDI), by contrast, did not display a statistically significant relationship with tax revenue. This finding suggests that its overall impact may be neutral or highly context-dependent, making it difficult to detect a systematic average effect across studies. A key insight from the moderator analysis is that the definition of the tax base matters profoundly. The relationship between several determinants (e.g., trade and agriculture) and tax revenue varies significantly depending on whether social security contributions are included (TRESSC) or excluded (TRISSC) from the revenue measure.
*Table 1. Meta-Analysis Results With Key Moderators*




Variable


Overall effect


TRISSC (Tax Excl. SSC)


TRESSC (Tax Incl. SSC)


Panel models


Static models


With corruption control




GDP


0.20***


0.002


0.194***


0.20***


0.239***


0.09***




Trade


0.068***


Insignificant


0.062***


0.053***


0.066**


0.055***




Agriculture


-0.185**


-0.361


-0.18***


-0.147***


-0.186***


-0.089***




Industry


0.079***


0.024


0.091***


0.071***


0.117***


0.09***




Inflation


0.03**


0.133


0.003


0.005


-0.013


0.023***




Corruption


-0.156**


0.038


-0.154***


-0.16***


-0.355***


-




Tax (t-1)


0.528**


0.53*


0.675*


0.566*


0.491*


0.381*




FDI


-0.019


-


-


-


-


-




*Note: *p<0.1, ** p<0.05, *** p<0.01. SSC = Social Security Contributions.*




Source: Results Research

Conclusion

This study offered a comprehensive synthesis of the determinants of tax revenue, demonstrating that economic structure (i.e., sectoral composition), the macroeconomic environment (e.g., trade and inflation), and institutional quality (especially corruption), play pivotal roles in shaping revenue outcomes. Importantly, the impact of these factors is not fixed or absolute; rather, it is significantly moderated by methodological choices and by how the tax base is defined. The findings can be translated into several clear policy implications. Governments should promote trade openness through well-designed, trade-liberalizing policies, as it can enhance revenue both directly and indirectly by expanding and formalizing economic channels. At the same time, agricultural taxation requires rationalization. Efforts should focus on formalizing the agricultural sector and reassessing blanket tax exemptions that may unintentionally create loopholes and narrow the tax base. In addition, a strategic emphasis on industrial development is also essential. Policies that support industrialization, particularly those enabling small and medium enterprises to scale up, can help create a more easily taxable economic base. Finally, combating corruption and strengthening institutions must remain a central priority. Improving governance and curbing corruption are indispensable for improving tax compliance and for increasing the overall efficiency of revenue collection.

Abstract Today, the significance of the presence and emergence of fintechs—particularly those active in the financial sector—is widely recognized. This importance is reflected in the growing number of recent studies that examine fintech performance and its relationship with macroeconomic indicators at the international level. Global experiences indicate that fintech has substantially contributed to promoting economic growth and controlling inflation by expanding access to financial services. In Iran, more than 50 active fintech companies have entered various areas of the banking business model, suggesting that their presence can influence macroeconomic performance. Enhancing economic growth has been a primary concern for policymakers in recent years, which raises several key questions. First, how does the emergence and presence of fintech impact economic growth? Second, does the impact of fintech on economic growth vary under different conditions of inflation, liquidity, exchange rates, and stock price index? Using time series data from 1991 to 2023, the present study aimed to examine these questions. The ARDL method was employed to assess both the short-term and long-term effects of fintech on economic growth. Furthermore, the threshold regression method was applied to examine the impact of fintech under different levels of inflation, liquidity, exchange rates, and stock price index. The results of the autoregressive method with a structural break indicated a positive effect of fintech on economic growth. The threshold regression results further revealed that the effect of fintech on economic growth would vary across different macroeconomic variables.

Introduction

The development of the financial sector is a key driver of economic growth and GDP expansion. Rapid digitalization and technological advancements—such as digital currencies, artificial intelligence, mobile payments, and online trading—have profoundly transformed the financial system. These innovations, collectively known as financial technology (fintech), not only reshape financial operations but also create new opportunities for investors. According to the Financial Stability Board (2021), fintech refers to technological innovations in financial services that have the potential to alter business models, products, and market structures. Fintech enhances financial inclusion, lowers transaction and transfer costs, improves income flows, and supports investment and productivity. Through these channels, it influences consumption, savings, employment, and wealth creation, thereby fostering economic growth. Building on the endogenous growth model, the present study aimed to analyze the impact of fintechs on economic growth using data-driven approaches inspired by Narayan (2019) and Mshamba and Gani (2023). Previous empirical research indicates both positive long-term and negative short-term effects, with some evidence suggesting a U-shaped relationship—initially negative but turning positive as fintech matures. To examine this behavior, four hypotheses were explored, each focusing on the role of macroeconomic thresholds: inflation, exchange rates, liquidity, and stock price index.

Materials and Methods

The study relied on annual macroeconomic and fintech data for the period 1991–2023 (1370–1402 S.H.) to examine the dynamics of fintech’s impact on economic growth within an endogenous growth framework. The number of active fintech firms served as a proxy for fintech activity, in line with World Bank (2022) measurements, which highlight firm creation as the most accessible global indicator. Two complementary econometric approaches were employed. First, the autoregressive distributed lag (ARDL) model was used to analyze short-term and long-term dynamics. Second, the threshold regression (TR) model was applied to capture nonlinear effects under varying macroeconomic regimes. Specifically, four threshold variables (i.e., inflation, exchange rates, liquidity, and stock price index) were considered to examine whether the impact of fintech on growth varies across these conditions. Economic growth was the dependent variable, while sectoral credit ratios and investment rates were considered as control variables. By combining these models, the study provided a comprehensive assessment of fintech’s impact on economic growth and its interaction with macroeconomic fluctuations.

Results and Discussion

The results demonstrate that fintech plays an increasingly significant role in the modern economy, operating alongside traditional banks and influencing key macroeconomic variables—particularly economic growth. Empirical evidence confirms that the relationship between fintech development and growth is nonlinear; with effects that can be either positive or negative depending on prevailing macroeconomic conditions. Using the ARDL approach, the study confirmed a well-fitted model in which fintech exerts an overall positive effect on economic growth. However, analysis of macroeconomic thresholds—inflation, exchange rates, liquidity, and stock price index—revealed important nonlinear patterns. When inflation or exchange rates exceed critical thresholds, fintech’s impact on growth becomes negative, primarily due to rising investment, increased operational costs in technology infrastructure, and reduced financial accessibility. Similarly, excessive liquidity can heighten inflationary pressures, thus undermining fintech’s positive effects. In contrast, across varying levels of the stock price index, fintech consistently demonstrates a positive effect, reflecting its role in enhancing market efficiency and investor confidence.

Conclusion

According to the findings, fintech’s impact on economic growth is contingent upon macroeconomic stability. This study addressed a significant empirical gap by highlighting these threshold-dependent effects. It concludes that future research should further investigate the nonlinear (potentially U-shaped) relationship between fintech and economic growth, particularly through interaction terms that link fintech with macroeconomic variables.

Abstract The present study aimed to examine the transfer, reception, and the spillover of volatility from March 1982 to September 2022, using the time-varying parameter vector autoregression model based on Barunik-Krehlik (TV-VAR-BK) with monthly frequency. The results indicated that the primary relationship among the volatility of the analyzed variables is of long-term nature, with the exchange rate emerging as the dominant factor in explaining the volatility of the examined network. In the short term, liquidity serves as the primary transmitter of volatility to inflation and the exchange rate. However, in the medium and long term, the exchange rate becomes the primary transmitter of volatility to inflation, while liquidity acts as the net receiver of currency volatility. Additionally, the long-term impact of the exchange rate is more pronounced. Failure to control currency volatility can lead to inflation turbulence by transferring volatility to liquidity, underscoring the significance of exchange rate stability in managing liquidity and inflation.

Introduction

The exchange rate is one of the key factors influencing inflation. In addressing the impact of exchange rate volatility, the status of inflation plays a crucial role (Tahsili, 2022). Moreover, assessing the factors influencing the exchange rate stands as one of the most challenging empirical problems in macroeconomics (Williamson, 1994). Since the exchange rate is significant economic indicator in any country, alterations in monetary variables (e.g., liquidity and inflation rates) as well as non-monetary variables can lead to fluctuations and instability in the exchange rate (Amrollahi et al., 2021). The causality of volatility between money and inflation can vary depending on economic conditions (Al-Tajaee, 2019). A deeper understanding of liquidity growth dynamics, inflation, and exchange rates in Iran elucidates the reasons behind high inflation, rapid and continuous liquidity growth, and the impact of exchange rate volatility. Extreme changes in each variable overshadow the others, indicating a complex relationship among exchange rates, inflation, and liquidity. Examining the relationship between the volatility of different assets unveils the phenomenon of volatility spillover, where fluctuations in one component trigger volatility in others. An additional crucial aspect is understanding the modes of transmission, reception, and intensity of the causal relationship among exchange rates, inflation, and liquidity in Iran during different periods. In different years, the mutual influence of these components may have varied based on political, economic conditions, health, and pandemic issues, each of which impacting decision-making concerning exchange rates, inflation, and liquidity as three vital macro-economic components. In this respect, the present study used the time-varying parameter vector autoregression model based on Barunik-Krehlik (TV-VAR-BK) with monthly frequency in order to examine volatility spillover from March 1982 to September 2022 in Iran, providing a new perspective on investigating causality by analyzing the time-frequency volatility among exchange rates, inflation, and liquidity.

Materials and Methods

This study is applied and analytical in terms of its purpose and research method, respectively. The data was sourced from the Economic Accounts Department and the National Accounts of the Central Bank. The TVP-VAR-BK model was employed to analyze the time series among exchange rates, inflation, and liquidity. The TVP-VAR-BK model helped analyze the transmission and reception of volatility of variables across different periods (short-term, medium-term, and long-term). Furthermore, the analysis delved into whether the variables acted as net receivers or net transmitters of volatility.

Results and Discussion

The results showed that, in the short term, liquidity exerted the most significant influence and transmitted volatility to other variables. Notably, the most substantial impact and transmission of volatility by the liquidity occurred in 2013, following the tightening of sanctions on Iran. In the medium and long term, the exchange rate emerged as the most influential factor on other research variables.
Examining the causal relationship in the short term, a strong causal connection was identified from liquidity volatility to inflation and the exchange rate. However, no causal relationship was observed between inflation and the exchange rate in the short term. Therefore, in the short term, liquidity could be the primary cause of volatility in inflation and the exchange rate. Failure to control short-term liquidity volatility could lead to severe volatility directly and indirectly within the studied network.
Moving to the medium term, the transfer of volatility was predominantly from the exchange rate to liquidity and, to a lesser extent, from liquidity to inflation. In the medium term, the transfer of volatility from the exchange rate to inflation was less pronounced. This suggests that fluctuations in the exchange rate strongly transfer volatility to liquidity in the medium term, and liquidity significantly contributes to the emergence of inflation volatility. The exchange rate, albeit to a minor extent, can directly contribute to the transfer of volatility to inflation. This underscores the dominant role of the exchange rate in the network during the medium term.
In the long term, no causal relationship between liquidity and inflation was observed, and there was no causality in the transfer of volatility between inflation and the exchange rate. This implies that factors other than the investigated network can explain inflation volatility in the long term. Although there is causality in the transfer of volatility from the exchange rate to liquidity in the short- and medium-term periods, this causality is stronger in the long term. Hence, while the classical view on liquidity and inflation holds until the medium term, the post-Keynesian view becomes evident in the long term. Overall, the exchange rate stands out as the dominant factor in the investigated network. Without stability in the exchange rate, Iran’s economy shall anticipate the fluctuating growth of liquidity and inflation in the short- and medium-term periods.

Conclusion

The primary relationship among the volatility of the examined variables proved to be long-term, with the exchange rate emerging as the dominant factor explaining the volatility within the investigated network. In the short term, liquidity functioned as the net transmitter of volatility to inflation and the exchange rate. However, in the medium and long term, the exchange rate takes on the role of the primary transmitter of volatility, while inflation and liquidity assume the positions of net receivers of currency volatility. Moreover, the impact of the exchange rate was found to be notably stronger. Should exchange rate volatility remain uncontrolled, it has the potential to induce inflation volatility by transferring it to liquidity. This underscores the critical importance of maintaining exchange rate stability for the effective control of liquidity and inflation.

Abstract High and continuous inflation in Iran's economy as a structural dilemma has adverse economic, political, and cultural outcomes, and to control the inflation, policymakers should employ appropriate and well-timed policies concuring to the economic structures of the country. Hence, this study points to distinguish and analyze the nature of inflation. For this reason, the present study examines the dynamics of the causal relationship between inflation and liquidity as well as the relationship between inflation and exchange rate by applying the continuous wavelet transform approach using monthly data during the years 1982 to 2021 in Iran’s economy. The results indicate: 1. Liquidity does not infulence the inflation rate in the long term and there is a reverse causality (causality from inflation to liquidity) and this result affirms the endogeneity of liquidity in the long term in Iran's economy. 2. The exchange rate growth shocks (from the supply side of the economy) affect inflation, in a way that the exchange rate altogether influences the inflation in both the short and long term.
1.Introduction
Amid the last few decades, high and steady  inflation has been a serious economic problem in Iran's economy. Empirical evidence suggests that in the years 1995, 1996, 2013, 2014, 2019, and 2020-21,  Iran's economy has suffered from heavy and sequentional inflations. However,  the perseverance of high inflation, especially since 2020, has turned into a fundamental problem. The main issue about the inflation in our country is not the inflation per se, but the critical status of it has faced development plans with great challenges for many years. Then again during the last decade, the economy tried to control inflation by restricting the growth of the money supply. But it appears that the results come to oppose established recommendations to curb the growth of liquidity.  Therefore, the question raised in the present study is whether the high inflation rate in Iran's economy is due to the rise of the money supply.
Although the relationship between inflation and liquidity in the economy has been examined in several studies, the significance of inflation and its relation with macroeconomic variables-  the broad previous and subsequent link with other variables- exaggerates the study of the relationships among these variables and other macroeconomic variables in different time scales. In this regard, the present study examines the relationship among some key monetary and price variables in the economy (dynamics of the relationship between inflation and liquidity as well as inflation and exchange rate).
2.Methodology and Methods
There are several methods to examine the interrelationships of inflation, exchange rate, and liquidity that are commonly divided into the form of statistical methods as well as model-based methods. But, since the causal relationship between these variables is likely to change over time, so further exploration of those relationships requires techniques that consider the relationship between two variables over time and different time horizons (different friquencies). Unlike most statistical and econometric techniques, the wavelet approach does not require variables to be survivable, nor does it assume linear relationships between them. In contrast to time series techniques, the use of wavelet approaches, especially wavelet coherence and continuous wavelet transform approaches within the framework of the methodology of econophysics (econophysics), opens new horizons in the study of causality in time series, because it shows the possibility of dynamically examining effects at different frequencies by separating it to the short and long term. To this end, the present study, using the continuous wavelet transform approach, examines the dynamics of the causal relationship between inflation and liquidity and the relationship between inflation and exchange rate by applying monthly data during the years 1982:1 to 2020:12 in Iran’s economy.
3. Discussion and Results
Generally speaking, based on what we've learned regarding the rooting of inflation in the our economy, it can be said that when the inflation rate increases and reaches a level higher than the average inflation (30 to 40 percent), such as when the average inflation rate shows lower figures, other monetary variables cannot be illustrative. Also, regarding the rooting of inflation, it can be said that in recent years, due to the adjustment policy, decrease of oil exports or sanctions, the demand for foreign currency exceeded its supply, and we witnessed instabilities in the exchange rate. Hence, the instability and fluctuations in the exchange rate and its concerned indicators do not exclusively follow monetary conditions.Therefore, the stability of exchange rates leads to the stability of prices and the limitation of monetary follow ups, and the resulting inflation itself causes more changes in the exchange rate in the next period.
4. Conclusion
In the current economic situation, the appreciation of the exchange rate is the cause of inflation and high inflation is to a noteable extent the cause of the budget deficit and liquidity growth. Therefore, another factor is the supply side that causes inflation and is not a monetary factor. Therefore, in a situation where the endogenous creative forces of liquidity are active, relying on controlling the amount of money and liquidity as the goal of monetary policy and a solution to curb inflation will not work and will pave the way for speculators and unproductive agents. Therefore, in order to achieve the price stability, it is recommended that the monetary policy maker should a) avoid  instant changes in relative and key prices (the most important of which is the exchange rate) and b) control the bank interest rate along with the structural reforms of the banking system in a way that the banking system moves toward optimal allocation of credit resources.

Abstract Studies conducted on the relationship between central bank independence and inflation show heterogeneity in the results. Some of these studies have concluded a negative relationship, while others have concluded a positive or insignificant relationship between central bank independence and inflation. The purpose of this study is to conduct a multilevel meta-analysis to examine the effect of central bank independence on inflation. For this purpose, all full-text articles that examined the relationship between central bank independence and inflation were reviewed. After reviewing the content and results, 58 studies were selected to enter the meta-analysis based on the meta-analysis protocol. Data from 58 selected studies included 619 regressions and 913 coefficients that were extracted and coded. In the first level of meta-analysis, the regression coefficients of each study were combined and the effect size of each study was calculated. In the second level of meta-analysis, to calculate the total effect size, the effect size of 58 studies was determined according to the weight of each study. The result of the combination and conclusion of individual studies shows that the independence of the central bank has a small negative and significant effect on inflation. The results also showed that the type of index used to calculate the degree of central bank independence affects the relationship under meta-analysis. In addition, the negative effect of central bank independence on inflation is greater in developed countries than in other countries.

Abstract The effect of exchange rate changes on the general level of prices is one of the major issues in macroeconomics and has important results for the monetary policy maker. With respect to these two variables in Iran's economy, modern econometric approaches can provide new insights. In this regard, using the threshold vector autoregressive model, the present study attempts to investigate the nonlinear exchange rate pass-through in Iran during 1369:1 – 1397:4. The results show that pass trough of exchange rate to the general price levels depends on the amount of inflation (inflationary conditions and its threshold). If seasonal inflation exceeds from 5.48%, the exchange rate shocks has lower effect on inflation. The results show that, exchange rate shocks have a severe effect. Due to the lack of inflation targeting policy in the Iran’s economy, the impact of exchange rate shocks on inflation is lower in values below the level of 5.48%. Accordingly, in inflation rates below the threshold, monetary policy has less freedom of action and the goals of reducing inflation and exchange rate policies need to be taken into account simultaneously.

Abstract The aim of this paper was to investigate the relationship between trade openness and inflation in selected developing and developed countries from 1990 to 2017 using a Panel data approach for testing Romer's hypothesis of relationship between inflation index and Trade Openness. The results of the paper show that the Romer hypothesis is rejected in both the studied groups (developed and developing). The results showed that the effect of trade openness on inflation rate was positive and significant in both groups. But the impact of trade openness on inflation has been greater in developing countries. The effect of money supply on inflation was positive and significant in both groups. According to other results of this study, GDP had a significant and negative effect on inflation. Also, the exchange rate has not been a determinant of inflation in developed countries but in developing countries it has had a positive effect on inflation.

Abstract The relationship between economic growth and inflation is one of the long-standing issues in macroeconomics, which is theoretically and politically confronted with many controversies. This is especially important for the Iran's economy, which seeks to achieve price stability and accelerate economic growth.  In this regard, the present study has used continuous wavelet transformation to provide a new insight into the relationship between economic growth and inflation with time-frequency analysis in 1369:2–1397:2. The results show that in the long run (more than 4 years), an increase (decrease) in economic growth is accompanied by a decrease (increase) in inflation. In addition, the increase in economic growth has caused inflationary pressures in limited form and in short run (1380-1383). Therefore, it is recommended that policy makers focus more on economic growth in the long run.

Abstract The exchange rate pass-through explains the relationship between changes in national currency and foreign trade of a country, while the responsiveness of trade to the currency changes depends on the perfect or imperfect degree of pass-through. The objective of this study is to analyze the effect of exchange rate pass-through on inflation in Iran as one of the main oil-exporting countries. To this end, we have specified a Structural Vector Auto-Regressive (SVAR) model including macroeconomic variables such as oil revenues, output gap, free market exchange rate, import prices, producer prices, consumer prices and money supply. To estimate the model, we have used quarterly data over the period 1991:1 - 2012:4.      Empirical results of the model estimation, which are in forms of impulse response functions and variance decomposition, have shown that although the degree of exchange rate pass-through to the price indices has been incomplete, changes in the exchange rate have led to fluctuations in the prices explaining partly Iran’s inflationary situation during the period under consideration. It also reveals the fact that a higher share of imported inflation implies the economy’s dependence on imports.

Abstract In this study, the continuous wavelet transformation approach is employed to test the dynamics of the causality between two principal inflation indices i.e. consumer price index (CPI) and producer price index (PPI) based on monthly data from 1990:5 to 2013:12 for the Iranian economy. Analyzing the dynamics of causality between these two inflation indices could provide significant policy implications. One of the dominant aspects of this approach compared with the conventional causality tests is that it has a higher ability in analyzing dynamics of causality between time series. The wavelet, as a band pass filter to the time series, is stretched in time by varying its scale, which makes it possible to show the short run and long run causalities between the time series. In this paper, we apply the continuous wavelet transformation to study the inflationary cycles of the Iranian economy. The results confirm both demand-pull and cost-push nature of inflation by indicating bidirectional causality between the CPI and PPI. In fact, the causality directions vary over time depending on different economic conditions.

Abstract Tracing the impact of exchange rate movements on prices is one the most important issues in monetary policy making. In this paper by applying a SVAR model to a quarterly data set spanning from 1990q1 to 2013q4, we assess the effect of exchange rate variations on domestic prices in Iran. In addition to exchange rate growth and output gap, the growth of liquidity, consumer, producer, and import prices are also included in the model. Our findings suggest that: i) There is an asymmetry in exchange rate pass-through in Iran. ii) Although small appreciations have no effect on prices, depreciations, especially large ones, are significantly effective. iii) The effect of exchange rate on consumer price growth, lasts for relatively longer periods of time.

Abstract Subsidies are known to distort prices, the optimal allocation of resources and economic growth and induce budget deficit and increase social costs, resulting in irreparable adverse effects on the economy. On the other hand implemetation of subsidy reform programs can have a widespread impact on economic aggregates  A clearly specified trend  in trajectory of macroeconomic variables is expected to better enable policy makers in planning for appropriate fiscal and monetary policy pakeges. The task of determining the best policy package, consistent with macroeconomic goals and constraints presents a genuine Stochastic Optimal Control problem. Solution for such a problem requires a practical statistical algorithm. The OPTCON2 method employed in this study seems to be a suitable method.  First, the econometric relationships among the macroeconomic variables of the model is estimated using 2SLS statistical method. Subsquently an OPTCON2 prorgram is specified using C # Language in a visual studio.    Simulation program  for subsidies during the 5th development plan indicates a decline in  economic growth for the first year, followed by a small rise in growth rate during the subsequent years.  The findings also indicates an initial rise in inflation  followed with a decline in later periods. It was also indicated that the unemployment rate is likely to rise in the beginning, leveling down to a given rate later.  

Abstract This paper focuses on the development of modern non-structural dynamic multivariate time series models and evaluating performance of various alternative specifications of these models for forecasting Iranian inflation. The Quasi-Bayesian method, with Literman prior, is applied to Vector autoregressive (VAR) model of the Iranian economy from 1981:Q2 to 2006:Q1 to assess the forecasting performance of different models over different forecasting horizons. The Bewley transformation is also employed for the re-parameterization of the VAR models to impose the mean of the change of inflation to zero. Applying the Bewley (1979) transformation to force the drift parameter of change of inflation to zero in the VAR model improves forecast accuracy in comparison to the traditional BVAR.[1]
[1]. Acknowledgement I would like to thank Paolo Girodani for comments and providing some GAUSS procedures, Ronald Bewley, David Forrester, Jan Libich, and two anonymous referees for their helpful comments and suggestions on an earlier version of this paper. Financial support from the Urmia University is gratefully acknowledged. The usual disclaimer applies. 

Abstract This paper intends to address the problem of inflation in less developed, and transitional economies, where the institutions of market is not fully developed. It is argued that the conventional Neo-Classical policies based on rigid Monetarist views fail to properly address the problem in less developed economies, and as a result its policy prescriptions are bound to fail.  In These economies the issue of persisting inflation and unemployment, presents a serious challenge, which requires a more realistic approach in studying the problem. Considering the case of Iran, following a brief review of the background of a dualistic structure in the economy, the nature of recent price changes and distribution patterns is analyzed for various income groups. Then it is argued that while the current price and subsidy reform could lead to higher economic efficiency, a significant success in this program requires however, supplementary macroeconomic reforms in several areas, towards the goal of greater economic growth and a more competitive position in global markets.   

Abstract One of the most fundamental outputs of social security systems is the redistribution mechanism. With moving from FUND to PAYG position and vice versa, the system shows intergenerational redistribuation and within-cohort redistribuation effects, depends on financial organization. According to the law, the mechanism considered for social security system in IRAN is FUND. Thus, we expect within-cohort redistribuation. This research tests this important note with evaluating insured individual accounts. The resualts show, in different target population deciles, internal rate of return (IRR) is 47 to 85% with average 53% and benefit – cost ratio (B/C) is 2.6 to 10.3 with average 3.7. This indicates that the necessary investment rate is 53%, while with current optimistic assessment, this rate is 30% for long-term, which shows intergenerational redistribuation. The effect inflation increase on redistribution test indicates current and future generation losses and also intensifying intergenerational redistribuation

Abstract   Using a vector autoregressive (VAR) model and an impulse response analysis, this paper investigates the impact of trade openness on main macroeconomic variables including growth of output, inflation, and employment for the period 1961-2007 in Iran. More specifically, we intend to study how an increase in the degree of openness affects these main macroeconomic variables. The results of impulse response functions show that in the short run the trade openness increases the output growth but decreases the inflation rate. However, the short-run impact of openness on the growth of employment is negative. Moreover, the results show that a one unit change in the standard error of trade openness has no long-run effect on the output growth, the inflation and the growth of employment

Abstract Using a vector autoregressive (VAR) model and an impulse response analysis, this paper investigates the impact of trade openness on main macroeconomic variables including growth of output, inflation, and employment for the period 1961-2007 in Iran. More specifically, we intend to study how an increase in the degree of openness affects these main macroeconomic variables. The results of impulse response functions show that in the short run the trade openness increases the output growth but decreases the inflation rate. However, the short-run impact of openness on the growth of employment is negative. Moreover, the results show that a one unit change in the standard error of trade openness has no long-run effect on the output growth, the inflation and the growth of employment. 

Abstract Investors in stock markets are concerned about the inflation effect on their returns. However, the impact varies based on investment horizons.  Since investors have different attitudes and diverse investment horizons, studying the relationship between inflation and stock returns in different time scales would have great implications for their investment. In this paper, we examine the Fisher hypothesis, which denotes a positive relationship between nominal stock return and inflation rate, using a wavelet multi-scaling method that decomposes a given time series on a scale-by-scale basis. The wavelet approach based on time-scale decomposition provides a valuable means of testing the Fisher hypothesis and resolves the problem of conflicting results in the literature. Our results show a negative relationship between inflation and the TSE returns in short-run horizon and a positive relationship in long-run horizon. 

Abstract Part of  harmful effects of inflation on the economy stems from the financial sector. This paper argues that inflation shifts resources from manufacturing sector to financial sector leading to an increase in the relative size of financial sector. This shift of resources can be viewed as a harmful effect of inflation, because if inflation were lower, the resources could be used directly to increase production of goods. Using Johanson's methodology and data of Iran in 1343-1385, we find that the relative size of financial sector is strongly affected by inflation. 

Abstract   Some studies show that in recent years, despite of increase in commodity prices such as oil and steel and conducting loose monetary policy in most countries, global price levels have low and stable rates of growth and inflation rates are well below the forecasts in Iran, in spite of adopting extremely expansionary policies, inflation rate has experienced a relatively stable trend in recent years. This may be due to globalization. This study aims at explaining theoretical bases of globalization effects on inflation and then evaluating it in Iran. In this study a VAR model has been used to test globalization effect on inflation, which mostly presents short-run dynamics of  inflation.  Results are as follow: 1- The more Iranian economy opens to trade the less domestic business cycles affect inflation and it will have a smoother path. 2-An increase in import price acts as a supply shock in the economy and increases inflation.3- Iran's trade partner's booms and slumps transmit to Iran through trade and affect domestic inflation.

Abstract The distributed lag effect of a unit change in one of the explanatory variables on the dependent variable is one of the major shortcomings of the standard linear egression model. The long run or error correction equation, with specifies a casual relationship between the inflation and its determinants, states that a unit change in one of the  explanatory variables can result in a change in the rate of inflation only during the period specified by the model. But in practice, changes in, for example, the country's money supply may affect inflation rate over a long period  This paper aims to estimate the adjustment path of the rate of inflation following exogenous monetary shocks. To do so, we use an ARDL model and time series data for the period 1961-2005 in the Iranian economy. The results indicate that one percent, once-and-for-all, increase in money supply positively affects the rate of inflation during three years. One percent increase in money supply at time t results in 0.42 percent in current period, 0.19 percent at time t+1 and 0.27 percent at time t+2 increase in the rate of inflation.    

Abstract This paper investigates the forecasting performance of different time-varying BVAR models for Iranian inflation. Forecast accuracy of a BVAR model with Litterman’s prior compared with a time-varying BVAR model (a version introduced by Doan et al., 1984); and a modified time-varying BVAR model, where the autoregressive coefficients are held constant and only the deterministic components are allowed to vary over time. Application using quarterly data of the Iranian economy from 1981:Q2 to 2006:Q1 shows that the performance of different specifications of time-varying BVAR models for forecasting inflation depends on the number of lags, hyper parameter that controls time variation, and forecast horizons. Our results, however, show that the modified time-varying BVAR model performs much better than other models regardless of the factors above.

Abstract In this paper we examine the effects of nominal variables on the GDP gap in Iran. The potential GDP is obtained by Prescott filtering method.    A VAR model is set up & estimated for GDP gap, inflation, market exchange rate growth, and liquidity growth. The results show that nominal variable shocks influence the GDP gap in Iran in the same direction. Stability of these shocks indicates their long-run effect on the system. Thus, for economic growth, the economic policy must concentrate on production increases, which would affect the long run production.  

Abstract The purpose of this paper has been to estimate the impact of price and non-price variables on non-oil exports of Iran. The non-oil exports are considred to be a function of monetary variables, such as the exchange rate, inflation rate, and two non-price variables, as productivity and competitiveness. We use the ARDL technique to estimate the relation. The results indicate that the non-price variables play a significant role in promoting non-oil exports in Iran. Free exchange rate and inflation rate, though had positive sign, are not very important. These findings indicate that in order to increase the non-oil exports, Iran has to remove the constraints on the efficient functioning of price variables and emphasis more on "productivity" and "competitiveness". 

Abstract This paper aims at estimation of own price elasticity, cross price elasticity and elasticity of saving with respect to income and price in the framework of the linear expenditures system (LES). Our findings show that aggregate marginal propensity to expenditure (MPC) is 0.72 beverange, fast food and tobacco products, and housing are 0.098 and 0.08, respectively.  The lowest MPC belongs to flour, cereal and bread with 0.028. Estimated income elasticity of goods and services dedicate that foods (excluding beverage, fast food and tobacco products) are necessity but housing, transportation, communication and entertainment are luxury. The price elasticity of saving reveals that any increase in flour and products, meat, milk and products, edible oils, fruits and vegetables, clothing and footwear will result in a decrease in the saving. The income elasticity of saving is 2.45.