Factorial, Personal, and Wealth Inequality in Peru, 1950-2016

F ,P I , P W , 1950-2016 Germán Alarco, a César Castilloa and Favio Leiva b Date received: September 5, 2018. Date accepted: December 22, 2018. Abstract Distribution of factorial income, personal income, and wealth in Peru is highly inequitable. In the 1960s, wage share was higher than at international average. It improved from the 1990s onwards, but without reaching previous levels. The corrected Gini personal income coefficient exceeded the official trend. The levels of inequality in productive wealth and assets distribution were higher than those of personal income distribution, in accordance with the international literature on the subject. A proxy of wealth distribution was elaborated, one which factored in both natural persons’ and businesses’ bank deposits in the national financial system. Some of the results are then compared with those of other Latin American economies. Keywords: factorial distribution of income; personal income; Gini coefficient; wealth distribution; financial system. 1. INTRODUCTION The problem of wealth and income inequality is again on the global economic agenda. The big entrepreneurs and politicians note that increasing inequality is a general trend, on the same level as the increase in societal polarization that elevates risks at a global level (WEF, 2018). The issue is on the IMF’s agenda, although its current political economic recommendations ignore it. Inequality is analyzed based on the personal distribution of income, rather than the factorial distribution from which it originates. Higher wealth and income inequality cause a variety of negative phenomena in economic, social and political contexts. The Peruvian economy is a middle-income economy with a population of 31.8 million inhabitants. In 2016, the nominal GDP per capita was US$6 049 and US$13 019, on par with buying power (Banco Mundial, 2018). Under the human development indicators (PNUD, 2017), the country is located at position 87 of 188 countries, and when corrected for inequality, it recedes to position 95, according to the data consulted to 2015. The economy in question is open to the exterior, with an external opening of 44.8% of the GDP, with free movement of goods and people. Between 1990-2017 under the new outwards-oriented development model, with a reduced presence for the State, a real growth of 4.6% yearly average was seen, similar to what was observed between 1950-1980 at an annual 4.8%—a period close to the golden age of capitalism, import substitutions and State-led industrialization. Currently, food and raw material exports are equivalent to 85.8% of the total exports in 2016 (BCRP, 2018), and there is a low inflation rate. Recently, given the induced economic deceleration, in addition to the fall in international prices of raw materials and lowering of taxes, the problem of inequalities in public finances has had a resurgence. Along with these macroeconomic indicators, governmental authorities offer information periodically regarding personal income distribution and, on occasion, distributive matters, considering the categories of gender, age range and geographic region. The official results regarding personal income distribution since the end of the 1990s have been positive, based on information from the National Household Survey (NHS). They demonstrate a decreasing tendency across time that allows for confirmation that the process of economic opening and liberalization has been positive in terms of equality levels approaching what is seen in economies with higher income per capita. Nonetheless, there is evidence that contradicts these results, because similarly to the majority of economies in the region, the monitoring and systematic evaluation of what happens with factorial (or functional) distribution of income is overlooked, and the distribution of the society’s wealth and assets is completely ignored. The circumscribing of the distributive problem in the personal sphere sidesteps the fact that, in a large part, this result of factorial distribution is established based on the economic or citizen agent’s position in productive processes, such as owner of means of production, employee or independent worker (beneficiary of mixed income), and will be closely linked to the distribution of wealth and productive assets.1 The foregoing was the perspective of classic economists such as Smith (1987), Ricardo (1959) and Marx (1972); later would come Kalecki (1956) and the post-Keynesians, who argue that the income distribution problem based on prices and salaries, degree of monopolization or profit margin, technology, and cost and productive structures are fundamental in determining levels of demand, output and economic growth. One recent discussion regarding this subject appears in Dutt (2017). Recently, certain IMF economists have noted that higher inequality erodes the possibility of sustainable economic growth (Ostry et al., 2014). Additionally, high levels of inequality fracture and disintegrate the social fabric, promoting phenomena such as greater instability, various forms of violence and even fostering corruption (Figueroa, 2010). In the political sphere, not only does it generate higher instability, but it goes hand in hand with the capturing of the State by the elite and economic groups that intend to redirect public policies to suit their own interests, putting democracy in a vulnerable position (OXFAM, 2016). The present work has a variety of objectives. Firstly, long series for the different components of factorial income distribution are reconstructed for the period from 1950-2016, as a follow up to previous lines of work (Alarco, 2017). The current series are established based on the most recent domestic accounts of 2007. Complete prior information exists for the previous base from 1994, and others starting in 1950, that should be made compatible. In the case of personal income distribution, and in particular of the Gini coefficient, official information exists from 1997 onwards. However, this data has been questioned by various authors, given that they are contradictions present in it, which also appear when compared to what is presented here. Finally, wealth and productive asset distribution is shown based on information from international sources, and constructed for this analysis based on family’s and business’ bank deposit distribution at the end of the 1990s. The information from these three distributive spheres, evaluated using the Gini inequality indicator, are presented and contrasted for the first time here. This exercise, which was calculated for Peru, could also be replicated for other regional economies. In this way, the following questions are expected to be answered: what are the inequality levels at the level of productive, factorial, and personal income wealth distribution in Peru? Do the results correspond to official information, and with each other? How can these results be interpreted, in light of comparable internationa (...truncated)