Graph of openness versus Industrial Pay Inequality for Japan and Australia
Figure 1: Trade openness vs industrial pay inequality in Australia
(Source: databank.worldbank.org, 2016)
Figure 2: Trade openness vs industrial the countries pay inequality in Japan
(Source: databank.worldbank.org, 2016)
Above graphs, show the trend in trade openness and industrial pay inequality in both the countries. Trade openness is the amount of trade as a percentage of GDP. The graphs have been drawn based on World Bank data. Industrial pay inequality data have been collected from UTIP-UNIDO.
(2) Interpretation of correlation
Correlation between the trade openness and industrial pay inequality has been calculated in the excel sheet based on collected data. For Australia, the correlation has been seen as 0.6749. This value implies that the correlation between Australian trade openness and industrial pay inequality is positive and high. Positive correlation depicts that movement of the variable are in the same direction (Jaumotte, Lall and Papageorgiou 2013). As shown in the graph, both the figures have increased from 1985 to 2005. Inequality in industrial pay in Australia has increased with increase in international trade in Australia. Correlation is more than 0.5, hence, it can be said that the correlation is high and trade openness and significant impact on industrial pay. When export increases, the expanding sectors demand for skilled worker. Therefore, wage in these sector increases. For the trickledown effect, as the export sector expands country’s GDP increases (Antras et al. 2012). When GDP increases, different sector of the economy increases due to having backward and forward linkages among the sectors. Consequently, inequality in the wage reduces (Stockhammer 2013). However, in Australia, the inequality is increasing as the share is industrial product in export is low compared to agricultural and mining product.
Correlation between Japan trade openness and industrial pay inequality is positive but significantly low, which is 0.055. Figure 2 shows that international trade is fluctuating with an increasing trend. Therefore, it can be said that trade openness in Japan has very little influence on industrial pay inequality. Japan has given priority to the industry in export. During the 1985 -1993, both the variables have moved to the same direction. However, after that there is no systematic correlation between these two variables.
(3) Analysis of data using Stolper-Samuelson theorem
Stolper-Samuelson theorem depicts the relation between relative output price and relative price of factors such as wage and capital cost. When relative price increases, return of the factor engaged in the production of that good also rises (Baldwin and Robert-Nicoud 2014). If labour is used intensively in production, real wage tends to rise. In each economy, both skilled and unskilled labour exists. Wage rate for skilled labour is high compared to unskilled workers due to having low productivity. Trade openness depends on reduction in tariff, removing license required for trade and other trade liberalisation policy (Benhabib and Nishimura 2012). Due to these factors, if export sector expands, the exported good price increases. Therefore, the demand for the input increases. The input may be labour or capital.
P = ar + bw, where r is the price of capital and wage is remuneration of worker.
Initially a sector expands by using relatively abundant factor, which has low cost. After openness of trade, increasing demand for intensively used input raises the price of that factor. For example, a country use labour intensively in production, trade openness will subsequently increase the relative price of the labour (PL/PC). Hence, increase in wage rate equalises the factor price across the country. However, Dabla-Norris et al. (2015) argued that rise in wage rate in export sector may increase regional wage disparity. High wage in different sector reduces inequality in wage.
However, the data of Australia and Japan economy shows that, wage inequality in industrial sector is low and steady in Australia compared to Japan. Relation between two variables follows the Stolper-Samuelson theory to some extent, however not justify fully. In Australia, the wage rate is higher and labour is relatively scarce (Baldwin and Robert-Nicoud 2014). Hence, the rate of immigrant in Australia is high due to attractive wage. Tariff in wage rate has suppressed the rate of immigration. Furthermore, trade in Australia is dominantly agricultural and mining. Therefore, increase in growth in net export has not able to mitigate industrial pay inequality in Australia.
On the other hand, industrial pay inequality in Japan has decreased overtime, however not in line with the increase in trade. During the year 1998-99, the percentage of pay inequality was very low. The country had experienced a fall in open trade during these periods. The demand for labour may surpass the supply of labour. According to Stolper-Samuelson theorem, trade openness and industrial pay inequality need to have negative correlation. Japan has experienced this for some period.
Jaumotte, F., Lall, S. and Papageorgiou, C., 2013. Rising income inequality: technology, or trade and financial globalization?. IMF Economic Review,61(2), pp.271-309.
Antras, P., Chor, D., Fally, T. and Hillberry, R., 2012. Measuring the upstreamness of production and trade flows. The American Economic Review, 102(3), pp.412-416.
Stockhammer, E., 2013. Why have wage shares fallen. ILO, Conditions of Work and Employment Series, (35).
Baldwin, R. and Robert-Nicoud, F., 2014. Trade-in-goods and trade-in-tasks: An integrating framework. Journal of International Economics, 92(1), pp.51-62.
Benhabib, J. and Nishimura, K., 2012. Indeterminacy and sunspots with constant returns. In Nonlinear Dynamics in Equilibrium Models (pp. 311-346). Springer Berlin Heidelberg.
Dabla-Norris, M.E., Kochhar, M.K., Suphaphiphat, M.N., Ricka, M.F. and Tsounta, E., 2015. Causes and consequences of income inequality: a global perspective. International Monetary Fund.
Databank.worldbank.org. (2016). World Development Indicators. [online] Available at: [Accessed 21 Sep. 2016].