In the era of the knowledge-based economy, despite the increasing speed of knowledge production and innovation, concerns about their effects on income inequality have also intensified. Regarding the causes of this phenomenon, the theories of skill-biased technological change (SBTC) and North–South trade (NST) have been proposed. The theory of SBTC seeks to explain the persistently widening wage gap between low-skilled and high-skilled workers in recent decades. Since the late 1970s, relative wages in labor markets have undergone major changes, steadily widening the wage gap in favor of more skilled workers. This theory suggests that technology substitutes for low-skilled labor, reducing employment shares and wages for low-skilled workers. Conversely, high-skilled jobs, for which technology is complementary, experience increased wages and employment shares.
 
Aim and Introduction
In the era of a knowledge-based economy, despite the increasing speed of knowledge production and innovation, concerns about their effects on income inequality have also grown. Two major theories explain the causes of this phenomenon: skill-biased technological change (SBTC) and North–South trade (NST). The SBTC theory seeks to explain the persistent widening of the wage gap between low-skilled and high-skilled workers in recent decades. Since the late 1970s, relative wages in labor markets have undergone major shifts, steadily widening the wage gap in favor of more skilled workers. This theory posits that technology substitutes for low-skilled labor, reducing employment shares and wages for such workers. By contrast, high-skilled occupations, for which technology acts as a complement, experience increased wages and employment shares.
Regarding the effect of trade expansion on income inequality, three main theoretical approaches have been proposed. The first approach—the neoclassical theory of international trade (the Heckscher–Ohlin standard model)—attributes trade between countries to comparative advantage resulting from differences in the abundance of production factors and inputs. The second approach, the new theory of international trade, explains trade relations among countries with similar factor endowments. Unlike the first approach, it assumes imperfect competition in the goods market and is used to explain trade among developed countries and trade within industries. The third approach focuses on technological change as a driver of trade patterns (Gorji & Borhanipour, 2008, p. 103).
In this study, the effects of trade expansion on income inequality are examined through the lens of technological progress. Trade expansion fosters knowledge and technology transfer, and by increasing innovation in the recipient (destination) country, it enhances productivity, added value, and production (Das, 2012, p. 621). This effect is especially evident in developing countries that rely heavily on research and innovation originating in developed economies (Piva, 2004, p. 1). Many economists regard the transfer of knowledge and technology through trade expansion as one of the key mechanisms influencing income inequality. Technological progress can affect skill premiums—and consequently income inequality—through three channels: knowledge spillovers, spatial agglomeration effects of innovation, and skill-biased technological change.
 
Methodology
To investigate and empirically analyze the effect of technology shock on income inequality in Iran, this research employs the computable general equilibrium (CGE) model. Specifically, the Partnership for Economic Policy one-period, one-country model (PEP-1-1) is used. This model comprises 98 equations and is divided into four blocks: price, production and trade, institutions, and system constraints. Necessary modifications were made to the standard model equations to align them with the structure of Iran’s economy. The PEP-1-1 model is based on data from the social accounting matrix (SAM) and incorporates economic activities, goods, production factors, and institutions.
To achieve the objectives of this study, scenarios were simulated by altering the value of the technology spillover coefficient and examining its effects on the Gini coefficient and the ratio of expenditures of the tenth to the first income decile, both indicators of income inequality. According to Briguglio (2008), the base value of the technology spillover coefficient for Middle East and North Africa (MENA) countries is 0.0062. In the simulation, this coefficient was incrementally increased by 0.1, 0.25, 0.3, 0.5, and 0.75 to assess its impact.
 
Results and Discussion
A comparison of simulation results for urban and rural areas reveals that, in both areas, increasing the technology spillover coefficient up to 0.25 reduces income inequality. Beyond this threshold, however, further increases in the spillover level lead to higher inequality. Based on the hypothesis of technology–skill complementarity, in Iran, an initial rise in the technology spillover coefficient increases productivity, production, and income, thereby reducing the wage gap. Once the spillover surpasses the 0.25 level, however, the absence of the basic skills required by advanced technologies, combined with a high degree of substitutability between unskilled labor and capital, leads to higher unemployment among low-skilled workers, reduced income levels, and greater income inequality.
 
Conclusion
Although higher levels of technology have the potential to reduce income inequality by increasing productivity and creating employment opportunities, their effects are complex and contingent upon factors such as the education and skill levels of the labor force, the nature of technological change, and the regulatory environment. Policymakers should take these factors into account and implement measures to ensure a homogeneous and inclusive distribution of the benefits of technological advancement.