Sadegh Mohit; Kowsar Yousefi; Salman Farajnia; Hossein Abbasinejad
Abstract
This study investigates labor market shocks in Iran using quarterly data from 2009 to 2022, employing a Bayesian sign-restricted Structural Vector Autoregression (SVAR) model to disentangle supply and demand shocks. The analysis evaluates the effects of monetary policy on these shocks across the ...
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This study investigates labor market shocks in Iran using quarterly data from 2009 to 2022, employing a Bayesian sign-restricted Structural Vector Autoregression (SVAR) model to disentangle supply and demand shocks. The analysis evaluates the effects of monetary policy on these shocks across the aggregate economy and three key sectors: industry, services, and agriculture. The real exchange rate is included as a control variable. The findings reveal heterogeneous responses to monetary policy across sectors. An expansion in the money supply positively affects labor demand in the industrial sector but negatively impacts it in agriculture. Moreover, interest rate reductions have a more pronounced employment-enhancing effect in industry compared to other sectors. In contrast, inflationary pressures dominate labor demand dynamics in agriculture and services. On the supply side, monetary shocks exert a negative effect on labor supply in agriculture—unlike in other sectors—likely due to persistently low wages, which reduce workers’ willingness to increase hours and encourage sectoral migration during inflationary episodes.
Introduction
The examination of Iran's labor market in recent years is of particular significance due to the young population, high labor supply, and lack of proportional demand growth, especially since the unemployment rate has consistently been above 10% from 1388 to 1398 (2009–2019), peaking at 14.7% in 1390 (2011). The decline in the share of employment in the agricultural sector and its shift to the industrial sector is another notable development in Iran's labor market over the past decade. Another current reality of Iran's labor market is the reduction in the economically active population, which has experienced significant fluctuations over the past ten years, dropping from 47.7% in 1384 (2005) to 41% in 1401 (2022). Analyzing this issue requires an examination of supply-side labor policies. Therefore, distinguishing the policy effects on the supply and demand sides of Iran's labor market appears essential for providing precise analyses.
Methods and Materials
In this study, supply and demand shocks are first decomposed, and then the effects of monetary policies on these supply and demand shocks in the labor market are examined using the results of this decomposition. The aim of this research is to separate supply and demand shocks, and given the macroeconomic nature of the question, it is necessary to employ macro econometric methods. Among the available methods, the use of the Structural Vector Autoregression (SVAR) model has been selected, and the model is identified using the sign restriction method, which is a modern approach for identifying coefficients and is defensible under methodological assumptions. This research utilizes the method proposed by Baumeister and Hamilton (2015) to identify supply and demand shocks in each sector. This method can be implemented in any market with available data on prices and quantities.
In SVAR models with sign restrictions, structural shocks are identified by imposing constraints on the signs of impulse responses (e.g., a positive demand shock increases both output and prices, while a positive supply shock increases output but decreases prices). Thus, structural decomposition is performed based on the applied sign restrictions. The process is as follows: first, a reduced-form VAR model is fitted to the data to obtain reduced-form parameters (coefficients and errors). Then, sign restrictions are applied to the estimated coefficients to enable their use in identifying structural shocks. This involves sampling rotation matrices that satisfy the sign restrictions on impulse responses. Finally, the time series of structural shocks are recovered by transforming the reduced-form errors using the identified structural transformation matrix. Labor market shocks were decomposed into supply and demand components using the sign restriction method within an SVAR framework, with parameter distribution updates conducted through Bayesian estimation. Subsequently, the real effect of money supply growth on the decomposed supply and demand labor shocks was analyzed using a panel model, with the exchange rate included as a control variable. The results of the model indicate that an increase in money supply has a positive effect on labor demand in the industrial sector across seasonal lags, while it has a negative effect in the agricultural sector.
Using the Household Expenditure and Income Survey, monthly household-level wages from 1388 to 1401 (2009–2022) were extracted, applying the current weighting aligned with the sampling weights of the Statistical Centre of Iran. Subsequently, wage data were adjusted for inflation using the Consumer Price Index (CPI) to obtain real wages. Since wages are collected monthly in this survey, the wage data were aggregated quarterly and classified into three economic sectors: agriculture, industry, and services, based on ISIC codes. Additionally, the number of working hours in the private sector was extracted quarterly from the Labor Force Survey data of the Statistical Centre of Iran at the household level for the years 1388 to 1401 (2009–2022). The data were then aggregated and integrated at the quarterly level, categorized by economic sectors according to ISIC codes. The growth rate of real wages and working hours has been calculated on a quarterly basis, and the analyses have been conducted using private sector data. Money supply data were extracted on a quarterly basis from the time series data of the Central Bank, and exchange rate data were obtained from the Gold, Coin, and Currency Information Network for the period from 1388 to 1401 (2009–2022). For the exchange rate, the data from the middle month of each quarter were used as a representative of the quarterly data.
Results and Discussion
In summary, a 1% increase in money supply leads to a 0.21% reduction in labor demand and a 0.15% reduction in labor supply in the agricultural sector. Additionally, a 1% increase in money supply results in a 0.09% increase in labor demand and a 0.16% increase in labor supply in the industrial sector. These findings collectively suggest that the interest rate reduction channel has a greater impact on increasing employment in industrial firms. In contrast, the inflationary effect dominates labor demand in the agricultural and service sectors. Concurrently, the exchange rate has the most significant negative impact on labor demand in the industrial sector and the least negative impact in the agricultural sector, indicating that the industrial sector is more affected by exchange rate fluctuations. On the labor supply side, only in the agricultural sector, due to low wage levels and despite the inflationary increase resulting from the money supply shock, individuals’ willingness to work decreases, leading to their migration to other economic sectors, such as industry and services.
The results of this study indicate the impact of inflation on the labor market, particularly in the agricultural sector. Accordingly, policymakers are recommended to focus on reducing inflation as a tool to improve labor market conditions on the supply side. Given the evident exodus of labor from the agricultural sector, as clearly observed in the results of this study, it is suggested that governing institutions prioritize implementing more supportive policies for this sector. Furthermore, considering the effectiveness of monetary policy through the interest rate reduction channel in the industrial sector, it is necessary to adopt appropriate policies to strengthen lending capacity in this sector to improve demand-side labor market conditions. The use of credit data and the impact of government fiscal policies for a more precise analysis of decomposed supply and demand labor shocks could be considered in future research.
Mansour Khalili Araghi; Hossein Abbasinejad; Yazdan Goudarzi Farahani
Abstract
The purpose of this paper is to study the welfare cost of inflation in Iranian economy by using dynamic models. An increase in inflation rate makes individuals to increase their desired level of real balance which in turn leads to an increase in the transaction cost and a decrease in the resources allocated ...
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The purpose of this paper is to study the welfare cost of inflation in Iranian economy by using dynamic models. An increase in inflation rate makes individuals to increase their desired level of real balance which in turn leads to an increase in the transaction cost and a decrease in the resources allocated to production of consumption goods. This issue can be analysed as the welfare cost of inflation. To reach that end, we first estimate the money demand function. The estimation is based on cointegration and dynamic least square model (DOLS). The estimation of money demand function is done with the aim of extracting parameters of income and productivity elasticity, parameter of money demand sensitivity to inflation. This estimation has been carried out by applying both static and dynamic models. In the static model, for an inflation rate of 10 percent, the welfare cost of inflation as a portion of income is 36.5 and for a dynamic model, it is 35.4. The results indicate that the central bank policies which have led to a reduction in the rate of inflation have had sufficiently reduced the welfare costs of inflation and this inflation rate is close to its Friedman-Rule value.
Hossein Abbasinejad; Yazdan Gudarzi Farahani
Volume 14, Issue 52 , April 2014, , Pages 26-1
Abstract
Abstract The study of the effect of memory in different economic indices, especially inflation and money market, has high research attractiveness. In this paper, by using the data of consumer price index for Iran during 1990/04 – 2011/11, we investigate the characteristics of CPI’s long–run ...
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Abstract The study of the effect of memory in different economic indices, especially inflation and money market, has high research attractiveness. In this paper, by using the data of consumer price index for Iran during 1990/04 – 2011/11, we investigate the characteristics of CPI’s long–run memory and regress its ARFIMA model. In addition, the amount of error terms in ARFIMA model are examined by FIGARCH model in order to determine what model the heteroscedasticity in inflation is following. The results indicate that monthly time series of inflation may have non-integer root. In other words, the degree of integration for inflation can be a non-integer number rather than an integer. To determine this, an Augmented Dikey-Fuller test, Philips–Prone test and KPSS are used and the results show that the degree of integration for inflation series should lie between zero and one. Thus, the hypothesis of inflation series with memory is proposed. By estimating the parameter of long run memory in the model it becomes evident that the inflation series has the degree of integration of 0.46 and one time differentiating leads to over-differentiation. Hence, inflation series has a long run memory in Iran and the effects of each shock on this variable exists for long periods.
Hossein Abbasinejad; Akbar Komeyjani; Ali Taiebnia; Ahmad Tashkini
Volume 10, Issue 38 , October 2010, , Pages 39-65
