| چکیده انگلیسی مقاله |
Introduction
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.
Methodology
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.
Results and Conclusion
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. |
| نویسندگان مقاله |
سید مهدی حسینی | Seyed Mahdi Hosseini Maasoum
Pre-doctoral research assistant, London School of Economics, London, UK.
دستیار پژوهشی در مقطع پیشا دکتری، مدرسه اقتصاد لندن (LSE)، لندن، انگلستان
امینه محمودزاده | امینه Mahmoudzadeh
Economics, Graduate School of Management and Economics, Sharif University of Technology, Tehran, Iran
گروه اقتصاد، دانشکده مدیریت و اقتصاد، دانشگاه صنعتی شریف، تهران، ایران
سید علی مدنی زاده | Seyyed Ali Madanizadeh
Graduate School of Management and Economics, Sharif University of Technology, Tehran, Iran
گروه اقتصاد، دانشکده مدیریت و اقتصاد، دانشگاه صنعتی شریف، تهران، ایران
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