The Impact of High-Tech Exports on Income: Findings on the Translog Production Function
Devran Şanlı, Aziz KonukmanThis study aims to present new findings to the literature by analyzing the impact of high-tech(HT) exports on revenue using panel data methods in 49 countries and under both Cobb-Douglas and Translog production functions for the period 1988- 2017. No other study has been found in the literature investigating the HT-Income relationship in the Translog production function. In this aspect, the current analysis is a pioneer study. Regression coefficients were estimated by the Driscoll-Kraay method, which produces robust standard errors in cases where OLS assumptions cannot be met. Furthermore, the existence of cointegration between the series was investigated by the stationarity of the residuals. According to the findings, the income elasticity of the physical capital contributing to the scale is 0.668; income elasticity of human capital was calculated as 0.584 and income elasticity of HT exports was calculated as 0.071. However, HT exports have been found to contribute to income per labor force, while human capital contributes to income per labor force along an increasing curve. The relationship between physical capital and income seems decidedly linear. These findings were tested for robustness with alternative regression methods in addition to the main models, and results compatible with the existing models were obtained.
Yüksek Teknoloji Ürün İhracatının Gelir Üzerine Etkisi: Translog Üretim Fonksiyonuna Dair Bulgular
Devran Şanlı, Aziz KonukmanBu çalışmanın amacı, yüksek teknoloji(HT) ihracatın gelir üzerindeki etkisini panel veri yöntemleriyle 49 ülke ve 1988-2017 dönemi için hem Cobb-Dougles hem de Translog üretim fonksiyonu altında analiz ederek literatüre yeni bulgular sunmaktır. Translog üretim fonksiyonunda HT-Gelir ilişkisini araştıran başka bir çalışmaya rastlanılmamıştır. Bu yönüyle mevcut analiz öncül bir çalışma özelliği taşımaktadır. Referans modelde SEK varsayımlarının karşılanamaması nedeniyle söz konusu problemlerin varlığında dirençli standart hatalar üreten Driscoll-Kraay yöntemiyle regresyon katsayıları tahmin edilmiştir. Ayrıca, seriler arasında eşbütünleşmenin varlığı artıkların durağanlığı ile araştırılmıştır. Elde edilen bulgulara göre, fiziki sermayenin ölçeğe katkısı olan gelir esnekliği 0,668; beşeri sermayenin gelir esnekliği 0,584 ve HT ihracatının gelir esnekliği 0,071 düzeyinde hesaplanmıştır. Bununla birlikte, HT ihracatının işgücü başına gelire azalarak artan, beşeri sermayenin ise işgücü başına gelire ise artarak artan bir eğri boyunca katkı verdiği tespit edilmiştir. Fiziki sermaye ve gelir ilişkisinin ise doğrusal olduğu görülmektedir. Bu bulgular ana modellere ek olarak alternatif regresyon yöntemleriyle sağlamlık kontrolünden geçirilmiş ve mevcut modellerle uyumlu neticeler elde edilmiştir.
When the growth processes of countries are examined, it is known that some countries perform much faster economic growth than others. In current growth theories, human capital and technology have become factors explaining growth and income differences Keynesian models give notice that growth can be achieved not only by increases in factors of production but also by reallocating existing resources from the inefficient non-export sector to the more productive export sector. According to this traditional view, an increase in export volume will have a positive effect on growth. The mentioned effect is experienced through foreign demand created by the increase in exports, resource allocation, economies of scale, technology diffusion, increasing total factor productivity, and contributing to free trade. One step further, it is argued that high-tech industries are the sectors that contribute the most to the international competitive performance of countries and that world trade in high-tech industries stimulates growth much more than in other manufacturing industries. Diversification of exports from primary goods to high value-added technology-intensive goods will allow more technological spillover to sectors than traditional product exports provide and will contribute to decimating the technology gap between countries.
This study aims to present new findings to the literature by analyzing the impact of high-tech(HT) exports on revenue using panel data methods in 49 countries and under both Cobb-Douglas and Translog production functions for the period 1988- 2017. The common point of previous studies is that they explain these relations under the Cobb-Douglas (C-D) production function. No other study has been found in the literature investigating the HT-Income relationship in the Translog production function. In this aspect, the current analysis is a pioneer study.
Regression coefficients were estimated by the Driscoll-Kraay method, which produces robust standard errors in cases where OLS assumptions cannot be met. Furthermore, the existence of cointegration between the series was investigated by the stationarity of the residuals. The stationarity of the regression residuals indicates that the estimated regression coefficients are not spurious and the obtained statistics can be interpreted with confidence. Since the series are cointegrated, regression analyzes can be interpreted in the long term.
According to the findings, the income elasticity of the physical capital contributing to the scale is 0.668; income elasticity of human capital was calculated as 0.584 and income elasticity of HT exports was calculated as 0.071. HT export-oriented technology-intensive policies will contribute positively to income.However, HT exports have been found to contribute to income per labor force, while human capital contributes to income per labor force along an increasing curve. The relationship between physical capital and income seems decidedly linear. When the substitution elasticities are examined, it is seen that the substitution relationship between physical and human capital is weak and there are complementary factors. Human capitalHT; physical capital-HT factors are factors that can be substituted for each other. These findings were tested for robustness with alternative regression methods in addition to the main models, and results compatible with the existing models were obtained.
The fact that human capital contributes to income along a curve that increases non-linearly emphasizes the importance of this factor for countries. This characteristic of human capital as the determinant of the condition of increased returns on the scale and the dominant factor determining income shows that the policies to increase high-tech exports recommended to countries to get out of the middle-income trap can actually be a supporting element that complements human capital. Therefore, policies that will basically increase the quantity and quality of education will both stimulate income growth and contribute to the reduction of social problems such as gender inequality.
Accordingly, policies must be designed for the establishment of technologyintensive free zones, the provision of the logistics infrastructure of these zones, encouraging foreign investment and trade, increasing institutional quality, etc.
