Modeling income inequality and openness in the framework of Kuznets curve: New evidence from China Abdul Jalil ⁎ , 1 School of Economic and Management, Wuhan University, Wuhan, 430072, PR China abstract article info Article history: Accepted 25 October 2011 JEL classification: F41 C32 O53 Keywords: Openness Income inequality Kuznets curve China This article tests the relationship between openness and income inequality in openness Kuznets curve frame- work. The Auto Regressive Distributed Lag (ARDL) estimator is employed to establish the long run relation- ship between openness and income inequality. We add to the literature by noting that Kuznets curve fits the relationship between openness and income equality in the case of China. This evidence is new and in line with the Kuznets hypothesis that income inequality rises with the increase of openness and then starts fall after a critical point. © 2011 Elsevier B.V. All rights reserved. 1. Introduction The government of China adopted a gradual policy of opening to the outside world in 1978. Since then the trade to GDP ratio raised from 8.5% to 67% and average tariff rates reduced from 49.5% to 8.5% along with 10% annual GDP growth. Indeed, this policy is one of the most im- portant policies in the modern history of international economics which paved a way for economic growth of China. The literature shows that there is a positive relationship between trade openness and economic growth of China (Jin, 2004). However, this economic growth and openness is accompanied with the increase in income inequality in the country. The Gini coefficient, a measure of income inequality, witnessed several peaks and troughs over the last six decades and went up from 22 in 1952 to 46 in 2009 (see Fig. 1). The Great Famine in early years, the Cultural Revolution with transi- tional phase to reforms from 1966 to 1978 and opening up to trade from 1985 to 2007 produced the peaks in the Gini coefficient. On the other hand, the land reforms in early periods, post famine recovery in early sixties and rural reforms from 1978 to 1984 were the major reasons of reduction of Gini coefficient. But Gini coefficient has been taking a sharp and apparently endless rise since 1985. This was the period of opening up to trade, foreign direct investment and higher financial de- velopment. Therefore, there is a view that the openness is one of the causes of income inequality in China. But a closer look tells that the in- come inequality is increasing with decreasing rate and the marginal ef- fect of openness on Gini coefficient is decreasing over the time (see Fig. 2). It is evident from Fig. 2 that there may be curvilinear relationship between openness and inequality. Therefore, it is possible that the openness variables may replace the economic growth in the Kuznets curve framework and income inequality may reduce as the openness reaches its turning point (Lee, 2010). The Kuznets curve postulates that the income inequality rises at the initial stage of economic growth and then improves after a certain point of economic growth. Dobson and Ramlogan (2009) and Lee (2010) note that openness may better be replaced the economic growth in the framework of Kuz- nets curve. In this paper, for the first time, the openness–inequality re- lationship is tested in the framework of Openness Kuznet's Curve for China over a time period of 1952–2009. We take five different variables to proxy the openness. This further adds to the novelty of this paper. The rationale for choosing China is quite obvious that China is perhaps the best example of the rising income inequality along with the increase in openness. The rest of the article is distributed into five main sections. Section 2 connects the study with the previous literature on openness and in- come inequality nexus. In Section 3, the detailed discussion on selecting the data and construction of variables for the empirical testing is pre- sented. The empirical model and econometric strategy have been dis- cussed in Section 4. The empirical results have been reported in Section 5, and finally in Section 6 conclusions have been drawn. Economic Modelling 29 (2012) 309–315 ⁎ Tel.: +92 51 90643044. E-mail address: jalil.hanif@gmail.com. 1 Currently the author is serving in School of Economic, Quaid-i-Azam University, Islamabad, 45320, Pakistan, Office Tel: +92 51 90643044. 0264-9993/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.econmod.2011.10.012 Contents lists available at SciVerse ScienceDirect Economic Modelling journal homepage: www.elsevier.com/locate/ecmod