Who are the Main Losers When Sanctions are Imposed?
Morteza Ghomi examines the impact of sanctions on the Iranian economy from 2011-2015, focusing on changes in the economic mobility of Iranian households.
This research note presents the main findings of a paper published online in the Economics & Politics Journal in December 2021. The original article can be seen at this link.
Since the 1979 Islamic revolution, Iran has experienced several rounds of sanctions mostly imposed by the United States and the European Union. However, the most severe sanctions against Iran were imposed in 2012. In January, the US defined sanctions targeting the Central Bank of Iran. In July, the EU imposed a total ban on imports of Iranian crude oil, impacting around one-fifth of Iran’s total oil sales. Finally, in October, the EU imposed financial sanctions on Iran, prohibiting most transactions between European banks and their Iranian correspondents. In the face of these sanctions, Iran’s currency lost about two‐thirds of its value compared to the US dollar, to which it was previously pegged (Ghomi 2021). In 2015, Iran reached a nuclear agreement with the P5+1, known as the Joint Comprehensive Plan of Action (JCPOA). The deal provided Iran broad relief from UN, EU, and US secondary sanctions, which were lifted in January 2016. This study investigates the aggregate and heterogeneous effect of the sanctions on Iran's economy between 2012 and 2015 and the impact on households.
The Aggregate Effects of the Sanctions
It is difficult to compare the economic performance of Iran with its potential path in the absence of the sanctions. Confounding factors in this period include the 1% drop in global GDP in 2012 and the roughly 60% drop in the oil price in 2014. These developments could have affected Iran's economy irrespective of sanctions. For that reason, I adopt the synthetic control methodology to measure the effect of sanctions on Iran's economy in 2012–2015. This method compares Iran with a counterfactual benchmark created using a weighted average of economic variables in similar countries. The result of this exercise suggests a considerable, severe, and persistent effect of sanctions on the Iranian economy. During the 4 years after implementation of sanctions until the JCPOA agreement, Iran's real GDP dropped significantly in comparison to its counterfactual, reaching a maximum divergence of 19.1% of GDP in 2015. The negative effect of sanctions persisted for 2 years after the removal of the sanctions and kept the Iranian economy more than 5% below its potential growth path. Gharehgozli (2017) shows a similar result for the first 3 years after the implementation of the sanctions.
Heterogenous Effect on the Poverty Mobility
To study poverty mobility, I use the household income and expenditure survey data provided by the Statistical Centre of Iran. Each year, the survey gathers data from 38,000 households including their social characteristics, living facilities, expenditures, and total income. The main shortcoming of this database is that the survey sample is updated each year and households cannot be directly compared in two different survey rounds. Using the methodology in Dang et al. (2014), I use time‐invariant characteristics to construct their income dynamics from the last year before sanctions (Iranian calendar year 1390) until the last year before the JCPOA agreement from (Iranian calendar year 1393).
According to the results, on average 5.8% to 9.6% of the households in the sample remained in chronic poverty, between 3% to 6.7% moved out of poverty, while 6.4% to 10.2% of households slid into poverty during the sanctions. In the poverty literature, this last group is usually denoted as the vulnerable group that needs social support to remain above the poverty line. Since government income dropped substantially during the sanctions years, vulnerable households lacked adequate support.
However, from both an economic policy and sociological perspective, it is important to understand the distributional effects of the sanctions. To compare the welfare change during this period using a simple poverty ratio can be misleading. Poverty mobility analysis is a preferable approach as it allows us to assess the nature of these changes and distinguish the issue of chronic poverty from that of more volatile poverty due to the distributive effects of sanctions. Different policy responses are needed to address chronic and volatile poverty.
The below table summarises the estimation results for mobility bounds. According to the results, households with a female head have a slightly higher rate of moving into poverty than households with a male head. Looking across different sectors of activity, households in which members are employed in the public sector suffered much less than those in which members were employed in the private sector, held no permanent jobs, or those dependent on other sources of income. Looking across different educational characteristics, those households headed by an illiterate person had the highest propensity to fall into poverty, likely due to a lack of financial literacy or employment prospects. Households characterised by high levels of educational attainment were the least likely to slide into poverty.
With respect to age groups, younger generations have a higher rate of moving into poverty. Also, there is a significant difference between the corresponding probabilities for religious groups, which supports the claim that religious minorities suffered disproportionately. To summarise, rural households, those without a permanent and stable job or those working in the private sector, households with less access to the public resources (like religious minorities), and households with young heads or heads with limited education have the highest rate of downward mobility into poverty.
Finally, I classify households based on their per capita expenditure before the sanctions and analyse how the mobility dynamics compare in those different quintiles in the pre‐ and post‐ sanctions periods. The upper bound estimates of this exercise are depicted in the figure below. When looking at the 0–20 percentile of the expenditure distribution, poverty mobility increased significantly during the sanctions period (2011-2015) relative to the period before sanctions (2008-2011).
Immobility for the lowest percentile group has increased from 33% in the 2008–2011 period to about 50% during the sanctions period of 2012-2015. Moreover, middle‐income households have a drastically higher rate of downward mobility compared to the pre-sanctions years. Households in the middle two income quintiles experienced between 39% and 48% mobility to a lower expenditure percentile, respectively, which is about 12 percentage points higher than the 2008‐2011 period.
Conclusion
In summary, accounting for poor domestic policies, sanctions have had a significant negative impact on the Iranian economy. Public sector employment and high levels of educational attainment reduce the likelihood that a household slides into poverty following the imposition of sanctions. This suggests that the economic consequences of the sanctions are inconsistent with claims that the measures are targeted at the government—vulnerable households are the main losers when sanctions are imposed. Policymakers in Iran should offer more support to vulnerable groups by providing more transfers or other forms of social support.
References
Dang, H.‐A., Lanjouw, P., Luoto, J., & McKenzie, D. (2014). “Using repeated cross‐sections to explore movements in and out of poverty.” Journal of Development Economics, 107(2014), 112–128.
Gharehgozli, O. (2017). “An estimation of the economic cost of recent sanctions on Iran using the synthetic control method.” Economics Letters, 157, 141–144.
Ghomi, M. (2021). Who is afraid of sanctions? The macroeconomic and distributional effects of the sanctions against Iran. Economics & Politics, 1– 34. https://doi.org/10.1111/ecpo.12203
How Did Sanctions Impact the Cost Efficiency of Iranian Banks?
Sajjad Dizaji examines the impact of sanctions on the performance of Iranian banks.
This research note presents the main findings of a book chapter titled “The Impact of Sanctions on the Banking System: New Evidence from Iran” in the Research Handbook on Economic Sanctions, edited by Peter A.G. van Bergeijk. The book chapter can be seen at this link.
To what extent have the imposed sanctions influenced the performance of Iranian banks?How has the Joint Comprehensive Plan of Action (JCPOA), before and after the US withdrawal, affected the efficiency of Iran’s banks? The results of stochastic frontier analysis show that, on average, the cost efficiency scores of Iranian banks show a decreasing trend over the last few years and increases in bank costs reflect the intense impact of sanctions. Moreover, the results reveal that although the JCPOA significantly decreased the cost inefficiencies of Iranian banks, this was only for a brief time period and only seen until before the US withdrawal from the agreement in May 2018.
Between 2006 and 2012, the United Nations Security Council, the United States, and the European Union levied several waves of increasingly severe unilateral and multilateral sanctions and restrictions on technology transfers, financial transactions, investments, revenue repatriation, and on various state and private entities in Iran. The sanctions intensified in 2012, when the US and the EU agreed to impose oil sanctions and impede Iran’s access to SWIFT worldwide messaging system used to arrange international money transfers.
With Iran cut off from the financial world, the Iranian rial significantly weakened through the years as inflation accelerated, eventually reaching IRR 12,350 to the dollar in June 2013 with an inflation rate of 45.1%. Access to capital in Iran was severely limited which forced the government to intervene in banks’ credit allocation. During this period, profitability and access to liquidity in Iranian banks fell substantially and the number of non-performing loans increased.
In May 2018, the US administration announced its unilateral withdrawal from the JCPOA, leading to significant inflation and pressure on Iran’s economy and banking system. While most Iranian banks were reconnected to the SWIFT network and could engage in international transactions, that again changed in 2018. The US Department of Treasury targeted 50 Iranian banks and their foreign and domestic subsidiaries. However, a key difference from previous rounds of sanctions was a lack of international support for the unilateral US approach, especially within the EU (Dizaji and Farzanegan, 2021).
Accordingly, a key question arises: how have the sanctions imposed since 2018 influenced the Iranian banking system? And what has been the impact of the JCPOA agreement on the efficiency of Iran’s banks?
Sanctions and the Capital Adequacy Ratio (CAR) of the Banking System
In March 2012, nearly all Iranian banks were disconnected from the SWIFT payment system. The capital adequacy ratio (CAR) of the banking system decreased from 8.4% in 2012 to 5.8% in 2015 (IMF, 2017:10). Figure 1 displays the CAR of Iranian banks between 2014Q1 and 2018Q2. This figure shows that in general CAR had a decreasing trend over this period. It fell from 8.9% in 2014Q1 to 4.5% in 2018Q2. There were exceptions in some quarters between 2016 and 2018 (i.e., 2016Q3, 2017Q1, and 2017Q2) where the trend was upward. It seems that the implementation of the nuclear agreement halted the decline of the CAR. However, following the US withdrawal from the nuclear deal (at the end of 2017 and beginning of 2018), the CAR continued its decline.
The Role of Sanctions Intensity
The difference between periods of unilateral and multilateral sanctions raises the question of whether the intensity of sanctions is significant to the impact on bank costs. In order to answer this question, a stochastic cost frontier model is used to analyse an unbalanced panel data for 12 Iranian banks (Eghtesad Novin, Tejarat, Karafarin, Mellat, Parsian, Pasargad, Refah, Saderat, Industry and Mine, Sarmayeh, Sina, Export Development). The unbalanced panel data includes thirteen years (from 2006 to 2018) where a dummy variable that captures the intensity of sanctions was used. This variable is coded as an ordinal variable (1–3) which includes three categories: limited sanctions (1) for the period 2016–2018; moderate sanctions (2) for the period 2006–2011; and extensive sanctions (3) for the period 2012–2015. Instead of using a mere dummy variable for economic sanctions, the three-part category ordinal measure better encapsulates the impact of the sanctions. Specifically, as extensive sanctions place comprehensive economic and financial pressures on the target economy, they should have a greater substantial impact than limited or moderate sanctions (see Caruso, 2003; Dizaji, 2018; Dizaji and Farzanegan, 2021).
The results confirm the increasing and statistically significant impact of sanctions on banks’ costs. According to the findings, an increase in the intensity of sanctions is associated with a larger increase in banks’ costs. Each level of increase in the intensity of sanctions with respect to the coding approach increases banks’ costs by approximately 6%, ceteris paribus.
Table 1 shows the average cost efficiency scores for 12 Iranian banks over the period from 2006 to 2018. Sina Bank has the maximum average cost efficiency score of 93.8%, while Parsian Bank shows the minimum average cost efficiency score of 55.8%. These numbers indicate that to operate efficiently, Sina Bank could only reduce its input costs by 6.2% while Parsian Bank could reduce its costs by 44.2% to reach the efficient frontiers.
Technical Efficiency Effects Model for Partial Lifting of Sanctions
I use a dummy variable to capture the impact of the nuclear agreement and lifting of some sanctions. It takes the value of 1 for the years 2016–2017, i.e., after the nuclear deal was implemented and before the US withdrawal, and 0 otherwise. The results show that the nuclear agreement between Iran and the world powers within the framework of JCPOA had a negative and statistically significant impact on Iranian banks’ costs before the US withdrawal from the nuclear agreement. Further analysis reveals that, after the US withdrawal, the JCPOA did not contribute significantly to Iranian banks’ efficiency. Moreover, the results indicate that both private and commercial banks performed better than government-owned and development banks during the sanctions period in terms of their total costs.
This study confirms the hypotheses regarding the positive impacts of sanctions on the Iranian banks’ costs and the negative impact of lifting sanctions (through the JCPOA agreement) on costs. The results indicate that the nuclear agreement between Iran and the world powers had been successful in reducing the Iranian banks’ inefficiency only when the US was involved in the agreement. However, after the US withdrawal, the JCPOA did not have significant contribution on banks’ cost efficiency.
Sajjad F. Dizaji appreciates the financial support from the Qatar National Research Fund and the support from Coventry University during his research.
References
Caruso, R. (2003), “The impact of international economic sanctions on trade: an empirical analysis”. Peace Economics, Peace Science and Public Policy, 9(2), Article 1.
Dizaji, S.F., (2021), The impact of sanctions on the banking system: new evidence from Iran, In: Bergeijk, P.A.G. van. (Ed). Research Handbook on Economic Sanctions, Edward Elgar. (pp. 330-350).
Dizaji, S.F., Farzanegan, M.R. (2021), Do Sanctions Constrain Military Spending of Iran?, Defence and Peace Economics, 32(2), 125-150.
Dizaji, S.F. (2018), Economic Diplomacy in Iran: reorientation of trade to reduce vulnerability. In Bergeijk, P.A.G. van & Moons, S. (eds). Research Handbook on Economic Diplomacy: Bilateral Relations in a Context of Geopolitical Change. Edward Elgar (pp. 273–296).
IFSB (2019), Data by Country. https://www.ifsb.org/psifi_03.php.
IMF (2017), Islamic Republic of Iran: Selected Issues paper, IMF country report, No. 17/63, February 2017.
What Were the Economic Costs of the Islamic Revolution and the Iran-Iraq War?
Mohammad Reza Farzanegan uses a synthetic control method to identify the effect of conflict on economic development by comparing Iran with a set of similar countries that did not experience the shocks of war and revolution between 1978 and 1988.
This research note presents the main findings of a paper published online in the journal Defence and Peace Economics in October 2020. The original article can be seen at this link.
Four decades ago, one of the major revolutions of the 20th century occurred in Iran, ending its system of monarchy. Mass protests and strikes intensified over the course of 1978, and in response, the Shah enforced martial law. He fled amid increasing unrest in January 1979. The monarchy collapsed on 11 February 1979. In September 1980, Iraq invaded Iran, and the world observed one of the longest ever interstate wars between two major oil producers (1980–1988).
What would Iran’s economy look like in the absence of revolution, war, and violence of that period? Gaining evidence-based insights into the economic costs of conflict and regime change is becoming more important, given the increasing tension between Iran and the United States, especially under Donald Trump’s administration.
A limited number of studies have examined the economic costs of the Iran-Iraq War. However, none has estimated the economic costs of war and revolution for the average Iranian citizen, in terms of lost income. I aim to do so by using a synthetic control method (‘SCM’), an approach which will help to identify the effect of conflict on economic development and quantify its economic size by comparing Iran with a set of similar countries that did not experience the shocks of war and revolution over the period of analysis (1978–1988).
Data and Model
I use SCM to construct a synthetic control unit for Iran, representing expected GDP figures under a scenario with no revolution, and no war after 1978. I refer to this control unit as “Synthetic Iran.” An outcome variable (in this case, GDP per capita in constant prices) should be comparable between Iran and its synthetic twin before the revolution and war with Iraq. In the case that the trends of outcome show a significant diversion between Iran and synthetic Iran after the shock, it becomes possible to make suggestions about the economic effects of the revolution and war. I will then be able to quantify this diversion, as well as the economic costs of conflict for an average Iranian.
To generate Synthetic Iran, I use country-level panel data for Iran and a sample of MENA and OPEC countries from 1970 to 1988. Restricting my set of potential control countries to the MENA region helps control for cultural, religious and geographical similarities. Considering OPEC members in generating Synthetic Iran makes sense, due to their common natural resource rent dependency.
For the outcome variable, I use GDP per capita in constant 2010 U.S. dollars. In order to have unbiased estimates of the post-revolution-war trajectory of Iran, the control countries for generating Synthetic Iran should not have experienced a main exogenous shock (e.g. war or revolution) from 1978 to 1988. To avoid such bias, I exclude countries affected by Iran’s revolution and war with Iraq. This eliminates Iraq itself. Israel and Lebanon also experienced a series of significant conflicts after Iran’s revolution. With these and some other adjustments (for example for missing data), 11 countries out of the initial 20 remain as possible candidates to generate Synthetic Iran.
The generated Synthetic Iran should have a comparable economic and demographic structure to Iran for the average period of 1970–1977 (1978 was selected as the treatment year, since revolutionary protests and large-scale strikes intensified during this year, leading to the collapse of the monarchy in February 1979). In particular, I use different predictors of real GDP per capita to generate Synthetic Iran before the joint treatment of revolution and war. These predictors are available for all included countries for the period of analysis (1970–1988) and are helpful in producing a counterfactual Iran with similarities to the real Iran before the shock.
Findings
Table 1 shows that Synthetic Iran is best generated by a weighted average of five countries, with Tunisia (56 percent), Venezuela (16 percent), Saudi Arabia (13 percent), Oman (12 percent), and Algeria (1.6 percent) having the highest weights. Table 2 shows the average pre-1978 values of the covariates for Iran and Synthetic Iran. The latter reflects the pre-1978 performance of the GDP per capita covariates for Iran relatively closely. Synthetic Iran is similar to actual Iran in terms of pre-1978 GDP per capita as well as the associated shares of imports, gross capital formation, final consumption (private and public) in total GDP, life expectancy, and population growth rate. Some similarities between the selected countries and Iran in the 1970s are shown in Table 2.
In addition to data on Iran and Synthetic Iran, I present an unweighted average of variables for countries with a weight > 0 during 1970–1977 in Table 2. The predicted outcome (real GDP per capita) in the pre-treatment period is very close between Iran and Synthetic Iran (with optimally selected weights, as shown in Table 1). However, there is a significant gap between the outcome of real Iran and the unweighted average of real income per capita for countries with weight >0. This shows the importance of using a Synthetic control method for this analysis, which generates our counterfactual Iran by assigning the optimum weights to relevant countries.
Figure 1 shows the GDP per capita trajectory of Iran and its Synthetic counterpart for the 1970–1988 period. Synthetic Iran almost reproduces the per capita GDP of Iran during the entire pre-revolution period, making it possible to closely reproduce the economic characteristics of Iran before the 1978 uprisings without extrapolating outside the support of data from the donor pool. My estimate of the effect of the revolution and war on the per capita GDP of Iran is shown by the difference between actual Iran and its synthetic twin (Table 3).
We can see that the two lines diverge from each other significantly after 1978. While per capita GDP falls in Iran, in Synthetic Iran, per capita GDP keeps its earlier path during the early 1980s. The difference between the two series remains significant towards the end of the sample period. My results therefore imply mainly negative effects from the revolution and war on the economic development of Iran.
Figure 2 shows the estimated income gap between Iran and synthetic Iran with confidence sets (lower and upper bounds). The negative effect of the joint treatment of revolution and war is statistically significant in 9 out of 11 years following revolution.
Conclusion
During 1978–1988, the average annual economic costs for an Iranian were USD 3,150. The lowest average annual cost was USD 1,572 (in 1978), while the highest annual financial burden is USD 5,135 (in 1981).
If Iran had not experienced the revolution and subsequent war with Iraq, it could have allocated oil revenues, in reality devoted to military spending, to education, health, and physical infrastructure instead, creating higher productivity in the long run (see Farzanegan 2011 for a study on oil and government spending in Iran, and Farzanegan 2014 for the nexus between military spending and economic growth in Iran).
Furthermore, the Islamic revolution and war affected the economic position of social classes in Iran, with significant consequences for economic development. Economic disruptions and negative growth rates, which were partly caused by the Iran-Iraq War (1980-88) led to a significant decline in the size of the middle class, with its lowest level coming in at just above 15 percent of the total population in 1988.
Political factionalism after the revolution was another negative factor for economic growth. According to Bjorvatn, Farzanegan, and Schneider (2013), since the Islamic Revolution, reformers, conservatives, and several other factions have been involved in a competition for political dominance in Iran. Bjorvatn et al. (2013) use theoretical and empirical methods and show that in the case of Iran, an increase in oil rents is negatively associated with economic development when the degree of political fractionalization is high. They also find similar results using a sample of oil-based economies worldwide (Bjorvatn et al., 2012). In a related study, using theory and panel regression analysis, Bjorvatn and Farzanegan (2015) show that resource rents can promote political stability, but only when political power is sufficiently concentrated. There is little evidence for the concentration of political power in the post-revolutionary period in Iran.
My study, and the others mentioned, show a significant income loss for Iranians, mainly due to the political instability associated with regime change and the destructive war with Iraq.
References
Bjorvatn, K., Farzanegan, M.R., 2015. Resource rents, balance of power, and political stability. Journal of Peace Research 52, 758-773.
Bjorvatn, K., Farzanegan, M.R., Schneider, F. 2012. Resource curse and power balance: evidence from oil rich countries. World Development 40, 1308–1316.
Bjorvatn, K., Farzanegan, M.R., Schneider, F., 2013. Resource curse and power balance: evidence from Iran. Review of Middle East Economics and Finance 9, 133–158.
Farzanegan, M.R. 2011. Oil revenues shocks and government spending behavior in Iran. Energy Economics 33 (6), 1055-1069.
Farzanegan, M.R., 2014. Military spending and economic growth: The case of Iran. Defence and Peace Economics 25, 247-269.
Farzanegan, M.R., 2020. The Economic Cost of the Islamic Revolution and War for Iran: Synthetic Counterfactual Evidence. Defence and Peace Economics. (in press).
Firpo, S., Possebom, V., 2018. Synthetic control method: inference, sensitivity analysis and confidence sets. Journal of Causal Inference 6(2), 1-26.
Photo: IRNA
Do Sanctions Really Constrain Iran’s Military Spending?
Sajjad Dizaji and Mohammad Farzanegan model the effects of sanctions on military spending in Iran demonstrates the impact of unilateral sanctions and multilateral sanctions.
This research note presents the main findings of a paper published online in the journal Defence and Peace Economics in May 2019. The original article can be seen at this link.
Do sanctions reduce the military spending in Iran? This is the question we sought to answer by modeling the effects of sanctions on military spending in Iran to investigate the impact of unilateral sanctions (where only the United States sanctions Iran) and multilateral sanctions (where the United States acts in conjunction with other countries to sanction Iran). The results show that the increasing intensity of sanctions dampens the military budget of Iran. But by separating unilateral and multilateral sanctions, we show that only multilateral sanctions have a statistically significant and negative impact on Iranian military spending.
The Trump administration’s effort to change the political and military behavior of Iran has raised the important question of the effectiveness of sanctions. Will banking, energy and economic sanctions imposed by the United States hinder the ability of the Iranian government to expand its military ambitions? This is not the first time Iran is experiencing sanctions pressures. The Islamic Republic has been subject to different kinds of political and economic embargoes, which were mostly imposed by the US government. However, there were particular periods in political life of Iran where other global powers, such as the European Union joined US sanction initiatives under the endorsement of the United Nations Security Council resolutions and through the imposition of their own sanctions regimes.
Beginning around 2005, Iran was subjected to a growing range of multilateral sanctions imposed by the US, the EU and the UN with involvement of other main economic powers. The most expansive of these sanctions were implemented in 2012 when the US and the EU agreed to impose an oil embargo against Iran and to restrict Iran’s ties to the global financial system. Following a series of intense negotiations and the compliance by Iran to international monitoring standards, most sanctions were lifted on 16 Jan 2016 as part of implementation of the Joint Comprehensive Plan of Action (JCPOA). Notably, Iran’s military expenditure reduced by 30 percent between 2006 and 2015, one of the highest percentage decreases in military spending globally.
In May 2018, however, president Trump withdrew from the JCPOA. He criticized the deal and claimed that the lifting of sanctions had helped Iran to expand its military budget and develop its nuclear-capable missiles, support terrorism, and cause havoc throughout the Middle East and beyond. The US administration has now reimposed sanctions lifted as part of the nuclear deal. However, the difference with earlier experiences is the lack of international agreement, especially among European governments, about supporting the Trump administration’s strategy given doubts over efficacy. The US has failed to gain support for its new sanctions from the main European powers (e.g., Germany, France and United Kingdom) as well as Russia and China. A timely question that arises is to what extent the now unilateral sanctions of the Trump administration will be successful in reducing the military spending of Iran.
Multilateral Sanctions Constrain Military Spending
The first figure below shows the historical development of military spending in Iran (in USD $m., at constant 2016 prices and exchange rates). We observe that the military spending under the multilateral sanctions from 2006-2015 is consistently falling while a similar consistent reduction is not observed during the prior period of unilateral sanctions (1979-2005). Following the implementation of the JCPOA and lifting of multilateral sanctions, we observe a rise in real military spending of Iran (2015-2017).
The Role of Sanctions Intensity
The difference between the unilateral and multilateral sanctions periods raises the question of whether the intensity of sanctions important for controlling the military spending. In order to answer this question we apply an ARDL approach to the evolution of military spending in Iran over the period of 1960-2017 using strategic and socio-economic determinants while focusing on the effect of the intensity of sanctions. For this purpose we use an ordinal variable (0-3) in our military spending equation, which includes the categories of no sanctions (0), limited sanctions (1), moderate sanctions (2), and extensive sanctions (3). This four-category ordinal measure better captures the impact of the sanctions. Specifically, because extensive sanctions place comprehensive economic and financial pressures on the target economy, they are expected to have a greater substantial impact than limited or moderate sanctions (see Caruso, 2003, and Dizaji, 2018a).
The results show that an increase in the intensity of sanctions is associated with a larger decrease in military spending both in short and long run. One level increases in the intensity of sanctions with respect to our coding approach decreases military spending in the long-run by approximately 33 percent, ceteris paribus. Moreover the estimations of the demand equation for Iran’s military spending show that while non-defense expenditures, political institutions and the average of Middle Eastern countries military spending have influenced Iran’s military spending negatively, trade openness and population increase military spending in Iran. Trade openness provides sufficient revenues for Iranian government to expand its military and non-military expenditures (Dizaji, 2018b). The extensive economic sanctions may change the political behavior of Iranian government in order to pay more attention to social expenditures at the expense of reduction in military expenditures (Dizaji and Bergeijk, 2013; Farzanegan; 2011 and Dizaji et al, 2016).
The Case of Unilateral Sanctions
Another way to look at sanctions is to note the number of states involved. Sanctions may imposed by one country (unilateral sanctions) or a group of countries (multilateral sanctions) against the target country. It is generally argued that multilateral sanctions, due to the cooperative and coercive behavior of players, are more likely to succeed compared to unilateral ones (Caruso 2003, and Dizaji 2018a).
To estimate the impacts of different types of sanctions on Iran’s military spending, we categorize Iran’s sanctions into unilateral and multilateral ones. This categorization leads us to understand how unilateral US sanctions, which are not supported by international community, influence Iran’s military spending. The estimation results confirm the hypothesis that multilateral sanctions have statistically significant effects on military expenditure both in short and long run. The impact of unilateral sanctions on military expenditure is also negative. However, the impact is not statistically different from zero. Multilateral sanctions in place reduce Iran’s military spending about 77 percent in long run, ceteris paribus.
We have also examined the impact of sanctions on Iran’s military burden (defined as the ratio of military spending to GDP). The overall results support the observed impact on spending. First, economic sanctions have negative impact on Iran’s military burden. Second, the more comprehensive the sanctions are the higher the contracting pressure they put on Iran’s military burden. Finally, while unilateral sanctions are not shown to influence Iran’s military burden significantly, the impact of multilateral sanctions is negative and statistically significant. These results remain robust when we also control for the oil rents as the main source of financing Iran’s military expenditures (Farzanegan, 2011 and 2014). The estimation results show that oil rents have been important drivers of Iran’s military spending.
Our findings have important implications for the current policies of the Trump administration. By pulling out from the Joint Comprehensive Plan of Action (JCPOA) in May 2018, the US government has started to impose a variety of economic sanctions on Iran. The announced purpose is to constrain the military complex in Iran and thereby address Iran’s regional activities. Our analysis, which is based on historical data, shows that the chances of success for the US sanction policy is statistically insignificant in both the short and long run.
Sajjad F. Dizaji appreciates the financial support of the Gerda Henkel Foundation during his visiting research and preparing this paper at the CNMS, University of Marburg. This policy note is based on a Dizaji and Farzanegan (2018).
References
Caruso, R., 2003. The impact of international economic sanctions on trade: an empirical analysis. Peace Economics, Peace Science and Public Policy 9(2), Article 1.
Dizaji, S.F., 2018a. Economic diplomacy in Iran: reorientation of trade to reduce vulnerability. In: Bergeijk, P.A.G. van & Moons, S. (Eds.). Research Handbook on Economic Diplomacy. Edward Elgar (pp. 273-296).
Dizaji, S.F., 2018b. Trade openness, political institutions, and military spending (Evidence from lifting Iran’s sanctions), Empirical Economics. https://doi.org/10.1007/s00181-018-1528-2
Dizaji, S.F., Bergeijk, P.A.G. van, 2013. Potential early phase success and ultimate failure of economic sanctions: A VAR approach with an application to Iran. Journal of Peace Research 50, 721-736.
Dizaji, S.F., Farzanegan, M.R., 2018. Do sanctions reduce the military spending in Iran? MAGKS Papers on Economics 2018-31, Philipps-Universität Marburg, Marburg.
Dizaji, S.F., Farzanegan, M.R., Naghavi, A. 2016. Political institutions and government spending behavior: theory and evidence from Iran. International Tax and Public Finance 23, 522–549.
Farzanegan, M.R., 2011. Oil revenues shocks and government spending behavior in Iran. Energy Economics 33, 1055-1069.
Farzanegan, M.R., 2014. Military spending and economic growth: The case of Iran. Defence and Peace Economics 25, 247-269.
Hufbauer, G. C., Oegg, B., 2003. The impact of economic sanctions on us trade: Andrew rose’s gravity model. International Economics Policy Briefs Nr. PB03-4, Institute for International Economics. Washington, DC. SIPRI, 2018. SIPRI Military Expenditure Database. Stockholm International Peace Research Institute. Solna.
How Can Public Investment Help Improve Iran’s Growth Potential?
Amir Sadeghi examines how increased public investment in Iran under different oil price scenarios can help Iran achieve higher growth.
This research note is adapted from a working paper presented at the conference of the International Iranian Economic Association in March 2018. The full paper can be seen here.
Since the early 2000s, growth in Iran has been insufficient to improve real GDP per capita incomes. Sanctions and negative oil price shocks led to budget tightening and a contraction in pro-growth spending. Investment in infrastructure has been cut in half since 2012.
Looking ahead, lower public investment could constrain Iran’s growth potential. On the other hand, it is possible that an increase in government revenue could be followed by an aggressive scaling up of public investment.
In this study, we look at various approaches (gradual, aggressive, and conservative) to scaling up public investment in Iran under different oil price scenarios (baseline and adverse) in order to analyze how Iran can increase its public investment to achieve higher growth while preserving a fiscally sustainable path that avoids explosive and unsustainable debt or excessively tight tax policies that would be impossible for the government to maintain in the long run.
Fundamentally, a relaxation of the fiscal stance to finance a large temporary increase in investment faces two hurdles. First, scaling up too abruptly leads to inefficiencies. For example, selected projects may be of lower quality, making the entire process more inefficient.
Second, increasing investment requires building fiscal buffers so that in case of adverse shocks, such as an unexpected decrease in oil revenue, the investment plan can still be carried out without compromising fiscal stability. Furthermore, scaling up investment may shift financial resources from the private to public sector and have a distortionary effect by increasing interest rates and crowding out private investment.
To that end, we define and examine multiple scenarios for investment scaling-up: (1) a “gradual” scenario, in which investment would increase by 3 percent of GDP over four years and would then remain stable at its 10-year, pre-sanctions (2002-2011) average of 5.2 percent of GDP; (2) a “conservative” scenario, in which the same increase in public investment takes place over eight years instead of four—before it reaches the same long-run level as in the gradual scenario; and (3) an “aggressive” scenario that, in three years, leads to the highest level of public investment in Iran in the past two decades—6.5 percent of GDP—before stabilizing at its long-run level.
We also define two oil price scenarios: In the “baseline” scenario, oil prices are assumed to reach $55 a barrel by 2021, while under the “adverse scenario,” oil prices never exceed $48 a barrel.
We use a dynamic stochastic general equilibrium model that includes a resource fund and a range of fiscal tools. The model also contains developing economy features, such as absorptive capacity constraint and public investment inefficiency, which makes the model suitable to study Iran. The model is calibrated to Iran using annual applications. The baseline calibration reflects the 2002-2011 average.
The simulations show that scaling up investment is viable under all scenarios. However, because gross debt remains on a declining path in the long run and accumulating wealth continues, the costs of an aggressive strategy are considerable in terms of the increased consumption tax rate to finance the investment scaling up and the exchange rate appreciation in the real exchange rate. Furthermore, because of absorptive capacity constraints and investment inefficiencies inherent in oil-exporting developing economies, the growth impact of an aggressive strategy does not significantly differ from a conservative or a gradual design. Meanwhile its costs, in terms of fiscal adjustment, are significantly higher, especially during periods when oil prices are low.
The government is better off with an aggressive investment approach—if it can improve the efficiency of public investment. An aggressive front-loading of public investment results in 0.9 pp of higher growth, relative to the growth that can be achieved under the gradual scenario. However, that comes at the cost of a 1 pp higher consumption tax rate than what would be needed with the gradual approach (2 pp in the adverse scenario) and 4 pp higher accumulation rate of public debt in the short run (10 pp in the adverse scenario). Furthermore, there will be a larger appreciation in the real exchange rate under the aggressive public investment scenario, eroding the competitiveness of the tradeables sector. Structural reforms that improve the efficiency of public investment lead to larger growth margin, due to expansion in public investment: 2.1 pp vs. 1.0 pp in the adverse scenario.
Effective investment means that only a fraction of total public investment turns into productive capital and as public investment increases, the rate of expansion in effective public investment declines. An improvement in investment efficiency has a significant positive impact on growth outcomes and leads to higher private consumption and investment. Rising efficiency, however, does not help with the size of fiscal adjustment required to close the fiscal gap.
Introducing an oil fund, on the other hand, shows that the size of the adjustment needed to finance the scaling up of capital expenditures is smaller if the government fully utilizes its financial assets. The depletion of the oil fund, however, comes with larger appreciation of real exchange rates and deterioration in the current account balance.
Overall, preserving fiscal sustainability in the case of investment scaling-up is a complex task. It puts pressure on government to increase taxes, which can neutralize the impact of fiscal spending on growth. It can also lead to higher debt, which can, through higher interest rates, crowd out the private sector.
To overcome these challenges and ensure that investment spending supports sustainable growth, two policies could be considered. The first is to increase non-oil revenue. This would help build space for development spending while preserving overall fiscal deficit objectives. Furthermore, increasing domestic revenue would help reduce dependency on oil revenue by increasing the share of current expenditure financed by domestic taxes and allowing more oil revenue to fund public investment. The second suggested policy would be to strengthen the government investment framework to improve the efficiency of investment spending. Furthermore, bringing a long-term perspective to fiscal policy formulation, particularly through the adoption of a medium-term fiscal framework, could be very important and helpful in managing oil price shocks.
Photo Credit: Bourse & Bazaar
Are Iranian SMEs Ready for International Business?
Laurent Sciboz conducts a survey of nearly 100 companies in Iran's textile sector establishing that Iranian SMEs are highly interested in foreign partnerships.
This research note is adapted from a Master’s Thesis submitted to the University of Geneva and University of Savoie Mont Blanc.
Academic research on Iranian managers is scarce, mainly because of the lack of business ties with foreigners and longstanding international sanctions. Relatively little is known about how Iranian managers, particularly those at smaller enterprises, perceive business collaboration with outsiders. In order to address this knowledge gap, we have conducted a major survey among Iranian managers in the industrial sector. The aim of this original research, conducted as part of studies at the University of Geneva and the University of Savoie Mont Blanc, is to help Swiss, and more broadly European, businesses better understand the expectations of Iranian small and medium-sized enterprises (SMEs). The goals of this research are as follows:
Address the perception of Switzerland by Iranian SME managers in the industrial sector
Identify the expectations of Iranian managers when entering into a partnership with a Swiss company
Outline the importance of informal networks and the role of the "in-group" aspect in Iranian culture
A quantitative survey was conducted covering 101 managers from the textile industry, based primarily in Tehran and Kashan. These managers represent 87 different companies, of which 97 percent employ less than 250 people and therefore qualify as SMEs.
This survey clearly indicates the willingness of Iranian SME managers to do business with foreign companies and reflects the belief of these managers in international cooperation. When asked about the importance of an international network of business partners, a resounding 99 percent considered such a network "very" or "extremely" important. Currently, international connections are being established: 87 percent of the surveyed managers say that foreign companies have approached them for potential partnerships.
When it comes to the kind of partnership discussed during business collaboration, ventures that require limited capital are favored: 85 percent of the respondents would likely opt for an agency or distributor partnership while 59 percent are likely to choose a licensing arrangement. Regarding the possibility of engaging in joint ventures, 47 percent of managers would likely pursue a joint venture in which they would be the majority partner. On this basis, international investors should opt for "light" partnerships at first, such as agency, licensing or distributor agreements.
It is also important to consider the prevailing hierarchical model of business when approaching Iranian managers. Combined with understanding the strong "in-group" dimension of Iranian SMEs, a foreign company’s primary mission will be identifying the primary decision-maker. Resources could be wasted if this person is not identified, and if equivocal communication were to skew perceptions or the understanding of terms and conditions, it could lead to failure.
Accessing the full range of networks will be the key success factor for conducting business with Iran. This is a prominent cultural component, and the kind of networks that are important to Iranian managers have been quantified and qualified in our survey. We have addressed professional, personal, institutional, and international networks.
The personal network, encompassing friends and family, is the standout for its importance and Iranian managers rely on it to address business opportunities. Another important feature of Iranian culture is the fact that the personal network often merges with the professional network. More than 90 percent of the Iranian managers consider their their colleagues to be "part of their family circle." These managers rely heavily on both their private and professional networks to generate and evaluate business opportunities. A resounding 99 percent consider a referral from their "close network" to be be "very" or "extremely" important. More than two-thirds of the managers surveyed consider their personal/professional network to be "very efficient" as a means of identifying credible business opportunities.
From a business perspective, we can conclude that Iranian managers are open for business, and they wish to expand their relationships with foreign entities. That being said, foreign companies hoping to engage Iranian SMEs will need to develop cultural skills, and develop an awareness of Persian culture, Islamic tradition, and sentiments regarding Westernization.
This will allow interested parties to mediate what sociologist Ronald Stuart Burt refers to as "structural holes within a network." The informal networks of all managers can be leveraged, not just the professional networks. This view of networks is similar to the concept of "social context" as described by sociologist Mark Granovetter in his seminal work Strength of Weak Ties. In this sense, economic transactions in Iran are embedded within informal networks.
In regard to the perception of Swiss companies, we noticed that surprisingly, innovation is the least-favored feature. It is more important to Iranian managers that Swiss companies are trustworthy, precise, and that they deliver quality.
Overall, the insights from this survey can help foreign companies develop an entry strategy by outlining Iranian managers’ expectations. Iranian SMEs are very interested in foreign partnerships, but their approach to business depends greatly on informal networks. It is therefore important that potential foreign partners can navigate cultural nuance in order to successfully navigate business relationships.
Photo: IRNA