Title: FORECASTING WAGES INEQUALITY IN RESPONSE OF TRADE OPENNESS IN PAKISTAN: AN ARTIFICIAL NEURAL NETWORK APPROACH.
Authors: ULLAH, IRFAN; QIAN, XUEFENG; SHAH, MUHAMMAD HAROON; REHMAN, ALAM; ALI, SHER; AHMED, ZEESHAN
Abstract: Pakistan liberalized its trade in different regimes and the recent trade reforms is CPEC project which is expected to reduce wages inequality of skilled and unskilled labor. This study forecasts wages inequality as a result of trade openness in Pakistan by using artificial neural network approach for the period 1991–2017. The empirical outcomes revealed that trade liberalization is influential factor for reducing wages inequality in Pakistan, and the forecasting results for 2019–2026 show a dynamic trend of wages inequality in the response to trade liberalization; however, in many of the years, the positive implication has been witnessed for the inequality.
Subjects: PAKISTAN; INCOME inequality; FREE trade; UNSKILLED labor; SKILLED labor; FORECASTING
Publication: Singapore Economic Review, 2023, Vol 68, Issue 6, p1875
ISSN: 0217-5908
Publication type: Academic Journal
DOI: 10.1142/S0217590820500058

FORECASTING WAGES INEQUALITY IN RESPONSE OF TRADE OPENNESS IN PAKISTAN: AN ARTIFICIAL NEURAL NETWORK APPROACH.

ULLAH, IRFAN; QIAN, XUEFENG; SHAH, MUHAMMAD HAROON; REHMAN, ALAM; ALI, SHER; AHMED, ZEESHAN