International Development Economics Associates Conference on Work and well-being in the 21st century SAASTA Lecture Hall, The Observatory, Johannesburg, South Africa Macroeconomics of wage-led growth Esteban Pérez Caldentey esteban.perez@un.org

Profit and wage-led growth What is the effect on macroeconomic performance of a change in income distribution towards profits (gross operating surplus) or wages (labor compensation)? A profit led regime is one in which a change in favor of profits has a favorable effect on the economy. If the shift towards profit has a negative effect on the economy, then the economy in question is in a wage led regime Aggregate impact on the economy Expansionary Contractionary An increase in the profit share Profit-led growth Wage-led growth An increase in the wage share Wage led-growth

Theory: A simple approximation to wage-led

𝐴𝐷=𝐶+𝐼+𝐺+ 𝑋−𝑁 =𝐶+𝐼+𝐺+𝑁𝑋 Wage led regimes are identified on the basis of aggregate demand and supply analysis Aggregate demand 𝐴𝐷=𝐶+𝐼+𝐺+ 𝑋−𝑁 =𝐶+𝐼+𝐺+𝑁𝑋 𝐶=𝑝𝑟𝑖𝑣𝑎𝑡𝑒 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝐼=𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 Aggregate supply 𝐺=𝑔𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝑁𝑋=𝑛𝑒𝑡 𝑒𝑥𝑝𝑜𝑟𝑡𝑠 𝐴𝑆= 𝐴𝑃 𝐿 𝑀𝑃 𝐿 𝑊 𝑁 𝐴𝑃 𝐿 , 𝑀𝑃 𝐿 =𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑎𝑛𝑑 𝑚𝑎𝑟𝑔𝑖𝑛𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 𝑜𝑓 𝑙𝑎𝑏𝑜𝑟 𝑊=𝑤𝑎𝑔𝑒 𝑟𝑎𝑡𝑒

𝐴𝐷=𝐶+𝐼+𝐺+ 𝑋−𝑁 =𝐶+𝐼+𝐺+𝑁𝑋 Wage led regimes are identified on the basis of aggregate demand and supply analysis Aggregate demand 𝐴𝐷=𝐶+𝐼+𝐺+ 𝑋−𝑁 =𝐶+𝐼+𝐺+𝑁𝑋 𝐶=𝑝𝑟𝑖𝑣𝑎𝑡𝑒 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝐼=𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 Aggregate supply 𝐺=𝑔𝑜𝑣𝑒𝑟𝑛𝑚𝑒𝑛𝑡 𝑐𝑜𝑛𝑠𝑢𝑚𝑝𝑡𝑖𝑜𝑛 𝑁𝑋=𝑛𝑒𝑡 𝑒𝑥𝑝𝑜𝑟𝑡𝑠 𝐴𝑆= 𝐴𝑃 𝐿 𝑀𝑃 𝐿 𝑊 𝑁 𝐴𝑃 𝐿 , 𝑀𝑃 𝐿 =𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑎𝑛𝑑 𝑚𝑎𝑟𝑔𝑖𝑛𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 𝑜𝑓 𝑙𝑎𝑏𝑜𝑟 𝑊=𝑤𝑎𝑔𝑒 𝑟𝑎𝑡𝑒

Variables Profit led Wage led Consumption No or small differences in propensities to consume Propensity to consume out of wages is higher than the propensity to consume out of profits Investment Investment is a function of profitability. Accelerator effect not important (related to propensities to cosume) Investment is not a function of profitability Accelerator effect is important (related to propensities to consume) Net exports Price competition is important High import income elasticity Price competition is not important Low import income elasticity Government expenditure Redistributive policies

Shifts the entire aggregate demand function Variables Profit led Wage led Consumption No or small differences in propensities to consume Propensity to consume out of wages is higher than the propensity to consume out of profits Investment Investment is a function of profitability. Accelerator effect not important (related to propensities to cosume) Investment is not a function of profitability Accelerator effect is important (related to propensities to consume) Net exports Price competition is important High import income elasticity Price competition is not important Low import income elasticity Government expenditure Redistributive policies irrelevant Redistributive policies relevant Changes the slope of the aggregate demand function Shifts the entire aggregate demand function

Empirical evidence

Growth of real wages (real compensation per employee)   Correlation between the rate of growth of real wages and GDP Growth of real wages (real compensation per employee) Growth of real GDP 1961-2016 1960-1970 1970-1980 1980-1990 1990-2000 2000-2012 2000-2007 Belgium 0.60* 4.3 5.0 1.5 1.7 0.6 4.9 3.6 2.2 2.3 Denmark 0.44* 4.2 1.2 1.6 0.7 1.3 1.9 2.5 0.8 Ireland -0.03 4.1 4.4 2.4 1.8 4.5 3.5 7.5 5.8 3.1 Greece 0.71* 6.3 3.4 -0.2 0.3 8.5 5.1 2.1 0.9 Spain 0.55* 7.1 -0.5 7.4 2.8 2.9 France 0.65* 5.2 3.7 5.7 3.9 2.0 Italy 6.0 1.1 0.4 0.5 4.0 Luxembourg -0.05 -0.4 0.1 2.6 4.6 4.7 Netherlands 0.52* 3.2 3.3 1.4 Austria 0.49* Portugal 0.37* 7.0 5.3 3.8 Finland 0.19** 4.8 Sweden 0.42* United Kingdom 0.28* 2.7 Norway 0.25* 1.0 -0.1 United States 0.40* 3.0 Japan 0.79* 0.2 10.2 Canada 0.08 Australia 0.15 5.4 Average 0.39* Median

Real Wages and Investment Country Real Wages and GDP Real Wages and Investment Real Wages and Exports   Low Frequency Medium Frequency High Frequency Coherence France 0.5 0.2 0.0 0.4 0.1 United Kingdom 0.7 Canada 0.55 0.15 Germany Italy 0.25 0.10 Australia 0.3 Japan 0.45 Dynamic Correlation 0.63 0.64 -0.1 0.75 0.60 0.6 0.65 -0,1 -0.5 0.8 -0.2

Average duration from peak to peak   Capacity Utilization Investment GDP Consumption Real Wages Exports Average duration from peak to peak United States 15.3 14.9 30.6 45.7 24.8 22.7 France 13.9 21.7 37. 5 24.7 34.0 16.9 United Kingdom 17.7 13.3 31.7 22.1 20.3 19.9 Canada … 20.2 38.0 42.0 27.3 23.8 Germany 23.6 17.1 22.3 15.4 Italy 14.5 20.8 22.6 15.1 Australia 14.0 18.5 20.4 47.5 25.4 Japan …. 11.8 15.0 12.8 14.7 18.3 Average 18.1 25.2 30.0 18.4 Average Amplitude from trough to peak 6 28 25 37 21 18 4 12 15 10 7 13 9 20 23 14 16 17 8 5 11 24 36 5.4 13.1 15.8 10.4 17.3

Real Wages and Capacity Utilization 0.77 0.87 0.51 … 0.63 0.55 0.42 United States France United Kingdom Canada Italy Australia Germany Japan Real Wages and Capacity Utilization 0.77 0.87 0.51 … 0.63 0.55 0.42 Real Wages and Investment 0.78 0.73 0.68 0.80 0.70 0.75 0.25 Real Wages and GDP 0.88 0.90 0.72 0.30 Real Wages and Consumption 0.85 0.89 0.74 0.81 0.39 Real Wages and Exports 0.65 0.76 0.79 0.26 0.46 Investment and capacity utilization 0.66 0.38 0.59 …. Investment and GDP 0.84 0.86 0.69 0.83 Investment and exports 0,62 0.67 0.28 Capacity utilization and GDP 0.52 0.50 0.61 Capacity Utilization and exports 0.64 GDP and exports 0.33 0.96

Distribution of wealth Wealth share (top 10%, 5% and 1%) Consumption Consumption propensities are different for different income segments and income (and wealth are highly concentrated) Distribution of wealth (Selected regions, 2018) Distribution of wealth Wealth share (top 10%, 5% and 1%) 10% 5% 1% Africa 89.7 83.8 73.1 48.7 Asia Pacific 90.1 85.9 71.0 40.6 Europe 83.6 70.0 55.4 31.2 LAC 81.9 71.4 60.2 39.2 North America 84.3 74.4 62.1 34.8 Chile: Income shares and GINI with and without capital gains and tax evasion 2004 2007 2012 2013 Share the richest 1% 28.4 30.6 30.0 27.4 Share of the richest 0.1% 12.4 14.8 13.1 13.4 GINI1 0.62 0.59 GINI2 0.55

Determinants of investment in Latin America Commodity prices and in GFCF (1990–2016) Real exchange rate and GFCF (1995–2017) Period Correlation coefficient 1990-2001 -0.1146 2002-2008 0.9890 2010-2016 0.3795 Correlation coefficient: -0.41 Monetary policy rate and GFCF (2005–2017) Economic activity and GFCF (1994-2017) Country Correlation coefficient Period Argentina -0.37 2005–2017 Brazil -0.17 2004–2017 Chile 0.25 Colombia -0.02 2006–2017 Mexico -0.28 1994–2017

The external sector The available empirical evidence and my own estimates point to the importance of income effects and the insignificance of relative price effects. Histogram of the variation of the effective real exchange rate (2010=100) for a sample of 93 countries (annualized quarterly data) 1980.1-2015.1). Histogram of the variation of exports and imports in volume (2010=100) for a sample of 176 countries (anual data, 1980-2014)

The external sector The distinction between GDP and income. Income (the sum of the wage bill and profits) can be expressed as a function of the domestic product (GDP), net factor payments to the rest of the world ( 𝑁𝑃𝑅𝑊 𝑡 ), and current transfers ( 𝐶𝑇 𝑡 ) and the terms-of-trade effect (TTE) ( 𝑋 𝑡 𝑃 𝑥 𝑃 𝑚 −1 ). 𝑊𝑁 𝑡 + 𝐵 𝑡 = 𝐺𝐷𝑃 𝑡 + 𝑁𝑃𝑅𝑊 𝑡 + 𝐶𝑇 𝑐 + 𝑋 𝑡 𝑃 𝑥 𝑃 𝑚 −1 Profit share for selected Latin American countries (2002, 2006, 2010 and 2014). In percentages. Countries 2002 2006 2010 2014 Argentina 65.4 58.5 ,,, Bolivia 59.4 65.6 67.7 65.7 Chile 53.3 60.9 59.8 55.9 Colombia 62.8 64.0 63.4 63.0 Paraguay 63.9 67.3 65.5 Peru 72.6 75.8 66.6 65.0 Venezuela 66.4 67.6 58.6

Diferential between Income and GDP as percentage of GDP (Selected economies of LA) Bolivia Chile Peru Colombia

Annual rates of change of income and GDP for selected LAC countries Bolivia Chile Colombia Peru

Global Banks as rentiers in the commodities markets “Until recently, Morgan Stanley controlled over 55 million barrels of oil storage capacity, 100 oil tankers, and 6,000 miles of pipeline. JPMorgan built a copper inventory that peaked at $2.7 billion, and, at one point, included at least 213,000 metric tons of copper, comprising nearly 60% of the available physical copper on the world’s premier copper trading exchange, the LME. In 2012, Goldman owned 1.5 million metric tons of aluminum worth $3 billion, about 25% of the entire U.S. annual consumption. Goldman also owned warehouses which, in 2014, controlled 85% of the LME aluminum storage business in the United States. Those large holdings illustrate the significant increase in participation and power of the financial holding companies active in physical commodity markets.” United States Senate Permanent Subcommittee on Investigations in their report on Wall Street Bank involvement with Physical Commodities (November, 2014, p.3)