جستجوی مقالات مرتبط با کلیدواژه « کارگاه های صنعتی » در نشریات گروه « اقتصاد »

The question of why different countries vary in terms of  per capita welfare, has always been a fundamental issue in economics. It is generally agreed within the economic literature that the disparity in per capita income among nations cannot be primarily attributed to differences in the production inputs. Instead, it seems that the main discrepancy lies in the total factor productivity (TFP) of each country.Another crucial question is what factors contribute to the differences in TFP. The related literature generally falls into two categories. The first suggests the problem is the lack of advanced technology usage. According to these theories, various factors, including detrimental government businesses in developing countries fail to utilize the recent technologies, which lead to lower TFP.The second, more recent line of thought emphasizes the heterogeneity and disparity of firms within each country rather than considering a representative firm for each nation. The "misallocation" literature builds on the idea that differences in TFP among countries not only depend on individual firms productivity but also on how production inputs are distributed among these firms.This research seeks to answer what factors contribute to the misallocation of physical capital in the Iranian economy. Such an unnderstanding is crucial to address misallocation and move towards optimal allocation, thereby enhancing productivity and welfare. However, it is first necessary to identify what factors cause misallocation as each one demands a distinct solution. Some of these factors are inherently optimal, such as misallocation caused by the firms technology heterogeneity or the presence of physical capital adjustment costs, which do not require any corrective action. In contrast, others result from disruptive government policies and a hostile economic environment that stifle the economy.

In order to address this research question, we utilize a general equilibrium model based on the work of David and Venkateswaran (2019), featuring heterogeneous firms. We estimate the parameters using panel data from industrial workshops from 2003 to 2013 (the most recent data available) and employ the Generalized Method of Moments (GMM). The estimation of structural parameters allows us to disentangle the influences of five misallocation-causing factors. These are: 1. Investment adjustment costs, 2. Information frictions, 3. Distortions, 4. Heterogeneity in firms mark-ups, and 5. Heterogeneity in firms technology. It should be noted that in this model, information frictions refer only to firm's uncertainty about its own future productivity, not macro-level uncertainty.One notable feature of this research is its consideration of several misallocation factors within a single model. As will be discussed further, concentrating on one misallocation factor without considering others could significantly bias estimates of that factor role. By incorporating multiple factors into a unified framework, we can obtain unbiased estimates of each factor. Choosing appropriate moments to match the data and the model is a major challenge in this process. David and Venkateswaran (2019) demonstrate that by selecting five specific moments, the model parameters can be estimated uniquely and without bias.Another strength of this study lies in its use of statistical data from the annual survey of industrial plants. Given the significant differences between smaller businesses and large corporations, along with the former considerable role in employment in Iran,studies based solely on large corporations cannot paint an accurate picture of the Iranian economy.

Our findings indicate that capital adjustment costs, heterogeneity in the production function, and heterogeneity in firms mark-ups are the three primary causes of misallocation in the Iranian economy, accounting for over 80% of the variance in average capital production. Furthermore, the results demonstrate that misallocation has grown during the study period, with a particularly notable increase after 2007 due to the growing impact of disturbances.

In recent years, attention to the importance of optimal energy consumption has significantly increased. Meanwhile, the manufacturing sector is one of the most energy consuming sectors and its energy intensity index has always been high. In this study, we use a seemingly unrelated regression estimator to estimate factors that affect energy intensity in manufacturing industries with ten or more employees in Iran. We compare energy-based industries and non-energy-based industries. The results of this study show that while energy prices are inversely related to energy intensity in both groups of industries, the effect of rising energy prices on reducing energy intensity in energy-intensive industries is much greater. The ownership structure and industrial concentration are also inversely related to the energy intensity of industry. More privatization and increased  industrial concentration will reduce energy intensity, especially in the energy-based industries. The effect of research and development costs on energy intensity was either not significant or, contrary to expectations, was directly related to energy intensity.

Shortage of electric power is a serious issue for production, especially for those that rely more on electricity. In this paper, we investigate the effect of non-distributed electricity (blackout) on Iranian industry. The sources are derived from two undistributed energy data collected from 39 distribution companies and database of industrial plants. The final panel data is from industrial plants during 1385 to 1392. Results indicate that a one percentage point increase in power outage for firms with average electricity share, decreases production and sales by 0.11 and 0.10 percent respectively, which is significant and quite robust. A smaller negative effect is also observed in production factors such as capital, materials, and productivity, but is not significant. The results also show that electricity and fossil fuels are substitutes. For the firms with average electricity share, the use of fossil fuels increases by 0.045 percent in response to a one percentage point increase in power outage.

This paper examines the effect of exchange rate increase on Iran's manufacturing industries labor demand for the period of 2001-2016, by using the dynamic panel generalized method of moments (GMM). The exchange rate influences the demand for labor through two channels: first, while an increase in exchange rate makes home products cheaper relative to foreign products, increases the manufacturing product demand and has a positive effect on labor demand. Second, an increase in exchange rates makes imported inputs more expensive and, consequently, increases production costs that decrease demand for labor. The net effect of employment changes that caused by the exchange rate depends on the sum of these two channels. The results of this study show that the net effect of increasing exchange rate on employment of manufacturing industries is negative and significant, which indicates the high dependence of the manufacturing process in manufacturing industries on foreign inputs.