Analysis of policy passivity in Iranian Economy Using Factor-Augmented Bayesian Vector Autoregressive Model (FABVAR)

Document Type : پژوهشی

Authors

• mahdi ghaemiasl ¹
• Mahmod Hossin Mahdvi Adeli ²
• shhab matin ³
• sayed mahdi mosavi barrodi ⁴

¹ Ph.D. of Economic Sciences, Lecturer in Economics Faculty, Kharazmi University, Tehran, Iran;

² Ferdowsi University of Mashhad, Iran

³ Ferdowsi University of Mashhad, Mashhad, Iran;

⁴ Imam Sadiq University (I.S.U.), Tehran, Iran

https://doi.org/10.22067/pm.v22i9.18746

Abstract

Iran has more than a century of history in exploration and production; the first successful exploration well was Masjid Suleiman-1 on May 26, 1908. Since then, based on the latest oil and gas reports, 145 hydrocarbon fields and 297 oil and gas reservoirs have been discovered in Iran, with many fields having multiple pay zones. Proved oil reserves in Iran, according to its government, rank fifth largest in the world at approximately 150 billion barrels as of 2014, although it ranks third if Canadian reserves of unconventional oil are excluded. This is roughly 10% of the world's total proven petroleum reserves.
Oil sector in most of oil exporting countries (such as Iran) is a state-run sector and oil revenues belong to government. Iran is an energy superpower and the Petroleum industry in Iran plays an important part in it. In 2004 Iran produced 5.1 percent of the world’s total crude oil (3.9 million barrels per day), which generated revenues of US$25 billion to US$30 billion and was the country’s primary source of foreign currency. At 2006 levels of production, oil proceeds represented about 18.7 percent of gross domestic product (GDP). However, the importance of the hydrocarbon sector to Iran’s economy has been far greater. The oil and gas industry has been the engine of economic growth, directly affecting public development projects, the government’s annual budget, and most foreign exchange sources. In 2009, the sector accounted for 60 percent of total government revenues and 80 percent of the total annual value of both exports and foreign currency earnings. Oil and gas revenues are affected by the value of crude oil on the international market. It has been estimated that at the Organization of the Petroleum Exporting Countries (OPEC) quota level (December 2004), a one-dollar change in the price of crude oil on the international market would alter Iran’s oil revenues by US$1 billion.
The main hypothesis of this study is that the government's dependence on oil revenues has been caused policy passivity in Iran's economy. Fiscal policy and monetary policy are the two tools used by the state to achieve its macroeconomic objectives. While for many countries the main objective of fiscal policy is to increase the aggregate output of the economy, the main objective of the monetary policies is to control the interest and inflation rates. Traditionally, both the policy instruments were under the control of the national governments. Thus traditional analyses were made with respect to the two policy instruments to obtain the optimum policy mix of the two to achieve macroeconomic goals, lest the two policy tools be aimed at mutually inconsistent targets. In case of an active fiscal policy and a passive monetary policy, when the economy faces an expansionary fiscal shock that raises the price level, money growth passively increases as well because the monetary authority is forced to accommodate these shocks. But in case both the authorities are active, then the expansionary pressures created by the fiscal authority are contained to some extent by the monetary policies.
In other word the central bank's monetary policy and fiscal policy of the government have a heavy reliance on oil revenues and budgeting and monetary changes, instead of being active and effective, have an affective and passive nature and are subject to oil shocks.
In this study in order to investigate this hypothesis, seasonal data of 1369:1 to 1389:4 of oil revenues, government expenditures (as a representative of fiscal policy), monetary base (as a representative of monetary policy), GDP, exchange rate and GDP deflator (as a representative of price index) in a Factor-Augmented Bayesian Vector Autoregressive model have been used. If a small number of estimated factors effectively summarize large amounts of information about the economy, then a natural solution to the degrees-of-freedom problem in VAR analyses is to augment standard VARs with estimated factors. In this paper we consider the estimation and properties of factor-augmented vector autoregressive models (FAVARs).
Results of impulse response function and variance decomposition clearly confirm the passive monetary and fiscal policy in the Iranian economy. In other words, among the variables of model, the most affected variables respectively are the monetary base and government expenditures. According to the authors, there are two basic ways to deal with policy passivity, which are sterilization and stabilization of oil revenues through the correct management of stabilization funds and diversification of exports. Sterilization is, not to bring all the revenues into the country all at once, and to save some of the revenues abroad in special funds and bring them in slowly. In developing countries, this can be politically difficult as there is often pressure to spend the boom revenues immediately to alleviate poverty, but this ignores broader macroeconomic implications. Sterilisation will reduce the spending effect, alleviating some of the effects of inflation. Another benefit of letting the revenues into the country slowly is that it can give a country a stable revenue stream, giving more certainty to revenues from year to year. Also, by saving the boom revenues, a country is saving some of the revenues for future generations. In addition Oil stabilization funds are usually designed to address the problems created by the volatility and unpredictability of oil revenues, the need to save part of the oil revenues for future generations or both.

Keywords

• Oil Revenues
• Monetary policy
• fiscal policy
• Factor-Augmented Bayesian Vector Autoregressive model

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