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Transcript
Lecture 4: Productivity, Output, and Unemployment in the short-run and long-run • Key issues • The short-run response of employment to technological progress is ambiguous – increases in productivity sometimes decrease unemployment and sometimes increase unemployment • In the medium to long-run increases in productivity are associated with lower unemployment • Technological progress leads to structural change – job creation and job destruction (“Creative destruction” has distribution effects) • Why some countries experience technological progress and others do not depends on institutions such as property rights Structure of lecture 1. Technological progress and AS and AD (in the short-run) 2. Productivity and the natural rate of unemployment (in the long-run) 3. Distribution effects of technological change 4. Institutions and technological change 1. Technological progress in short-run: Production Function A production function with technological progress can be written as: Y F ( K, AN ) Leaving aside matters concerning capital, then: Y AN Output is produced using only labor, N, and each worker produces A units of output. Increases in A represent technological progress. A has two interpretations: 1.A indicates the state of technology 2.A indicates the degree of labour productivity i.e. Y/N Furthermore, employment is equal to output divided by productivity: N=Y/A That is, given a certain level of output, an increase in productivity decreases the level of employment needed to produce such output. Key question: When productivity increases does output (Y) increase enough to avoid a decrease in employment (N) (s-r: answer is ambiguous; l-r: answer is yes) Technological Progress, AS and AD, in the short-run •Recall the basic structure of the aggregate supply and aggregate demand model (Fig 13.1): – Output (Y) is determined by the intersection of the aggregate supply curve and the aggregate demand curve. (At Y there is equilibrium in labour, goods and financial markets) – The aggregate supply relation gives the price level for a given level of output. Upward sloping (YP) as an increase in output leads to an increase in employment, which leads to an increase in nominal wages and an increase in the price level. – The aggregate demand relation gives output for a given price level. Downward sloping (YP) as an increase in the price level leads to a decrease in the demand for output i.e. on increase in prices leads to a decrease in real money stock (M/P) resulting in higher interest rates, decreased demand and decreased output. Technological Progress, Aggregate Supply, and Aggregate Demand Figure 13 - 1 Aggregate Supply and Aggregate Demand for a Given Level of Productivity The aggregate supply curve is upward sloping: An increase in output leads to an increase in the price level. The aggregate demand curve is downward sloping: An increase in the price level leads to a decrease in output. What happens to AS-AD if productivity (A) increases? • AS curve shifts DOWN (Fig 13.2) – as the effect of productivity increase is to decrease the amount of labour needed to produce a unit of output (reducing costs), therefore prices are reduced at each level of output and AS • AD curve shifts UP or DOWN – depending on what triggered the increase in productivity: – Case 1: wide implementation of new technology AD as demand increases at the given price level due to consumption increases on prospect of future growth, investment increases due to prospect of higher future profits (exogenous change in productivity) – Case 2: more efficient use of existing labour and technology (or downsizing due to trade) AD which may lead to reduced consumption Technological Progress, Aggregate Supply, and Aggregate Demand Figure 13 - 2 The Effects of an Increase in Productivity on Output in the Short Run An increase in productivity shifts the aggregate supply curve down. It has an ambiguous effect on the aggregate demand curve, which may shift either to the left or to the right. In this figure, we assume that it shifts to the right. The effect of technological progress on output and employment • As per Fig13.2 even in Case 1 where technological progress leads to increased supply and demand and there is an unambiguous increase in equilibrium output (i.e. low costs and high demand lead to Y), it is not clear what happens to employment (as N = Y/A) • % change in employment (N) = % change in output (Y) - % change in productivity (A) • Condition employment will increase if % ΔY > %ΔA (i.e. if productivity increases by 2% then output must increase by at least 2% to avoid a decrease in employment) • Conclusion: in the short-run an increase in productivity may or may not lead to an increase in employment (theory does not settle the issue) The Empirical Evidence in the short-run • Fig 13.3 plots productivity growth and output growth in the US from 1960 to 2005 • It shows a strong positive relation between output growth and productivity growth • Also generally ΔY>ΔA which should be positive for employment levels The Empirical Evidence (short-run) Figure 13 - 3 Labor Productivity and Output Growth in the United States since 1960 There is a strong positive relation between output growth and productivity growth. But the causality runs from output growth to productivity growth, not the other way around. The Empirical Evidence (short-run) • But, empirically there is a problem as in the shortrun the causal relationship runs from output growth to productivity growth (not from productivity growth to output growth) • As demand rises firms use existing labour more intensively and there is higher productivity (but this is not due to the introduction of a new exogenous technology) (referred to as “labour hoarding” during bad times) • Conclusion: The empirical finding is ambiguous – sometimes in the short-run an increase in productivity leads to increased output and employment (and sometimes it does not) 2. Productivity and the Natural Rate of Unemployment (long-run) • Key question: Is the medium to long-run natural rate of unemployment affected by productivity changes? • A naïve argument is that of Technological unemployment—a concept associated with the technocracy movement during the Great Depression (and Luddites and Saboteurs)—that unemployment comes from the introduction of machinery. • In its crudest form, the argument that technological progress must lead to unemployment is false, as there have been large increases in the standard of living and in employment in advanced countries during the 20th century e.g. US and Japan have had highest productivity growth and lowest levels of unemployment in OECD. • A more sophisticated version of the argument cannot, however, be dismissed so easily. That is that perhaps periods of fast technological progress are associated with a higher natural rate of unemployment, and periods of slower technological progress are associated with a lower natural rate of unemployment. (To answer this, it is useful to analyse how price setting and wage setting are effected by changes in productivity.) Price Setting and Wage Setting Revisited • Consider price setting: – From Y=AN, each worker produces A units of output i.e. producing 1 unit of output requires 1/A workers. – If the nominal wage is equal to W, the nominal cost of producing one unit of output is therefore equal to (1/A) W = W/A. – If firms set their price equal to 1+ times cost, the price level is given by: W Price setting P (1 ) A – It can be seen that an increase in productivity (A) reduces costs, which has the effect of decreasing the price level (P) given the nominal wage (W) Price Setting and Wage Setting Consider wage setting: Wages are typically set to reflect the increase in productivity over time (i.e. if productivity has been rising by 2% a year for some time wage increases will rise by 2% per year): Wage setting W A P F (u, z ) e e Wages depend on the following factors: – Workers care about real wages, not nominal wages, so wages depend positively on the (expected) price level, Pe. – Wages depend negatively on the the unemployment rate (u) – Wages depend on institutional factors (z) – Wages also depend positively on the expected level of productivity, Ae. Price-setting (Fig 13.4) • The natural rate of unemployment is determined by price setting and wage setting relations • A condition of the natural rate is that expectations are correct i.e. Pe = P and Ae =A • The price setting equation can be reorganised as follows: W Price setting P (1 ) A W A P 1 • As A increases, the real wage paid by firms, W/P, increases one for one with productivity, A i.e. higher productivity (A) means lower prices set by firms (P), given the nominal wage (W), therefore, the real wage (W/P) rises . • This is outlined in Fig 13.4 where shift from A to A’ leads to a rise in real wages (but no change in the natural rate of unemployment) The Natural Rate of Unemployment Figure 13 - 4 The Effects of an Increase in Productivity on the Natural Rate of Unemployment An increase in productivity shifts both the wage and the price-setting curves by the same proportion and thus has no effect on the natural rate. Wage-setting (Fig 13.4) • Under the condition that expectations are correct, then Pe=P and Ae=A, the wage-setting equation becomes: Wage setting W A P F (u, z ) e e W AF (u, z) P • The real wage (W/P) depends on both the level of productivity and the unemployment rate. • In Fig 13.4 the real wage (W/P) is a decreasing function of the unemployment rate i.e. as u therefore W/P • If A rises to A’ then the real wage (W/P) rises for any given natural rate Response to a rise in A (Fig 13.4) • Suppose A increases by 3%, so A’ = 1.03 x A • The real wage (W/P) increases by 3%, this is implied by the A upward shift in the price setting curve given by: W P 1 • The wage setting curve also shifts up 3% at a given natural rate W of u, and W/P increases as per: P AF (u, z) • At B’ both curves shift up proportionally and the real wage is higher by 3% and the natural rate of unemployment remains the same (Fig13.4) • Conclusion: A 3% rise in productivity leads firms to reduce price by 3%, leading to 3% increase in real wages (due to price setting and confirmed by wage setting), with natural rate of unemployment unchanged Empirical Evidence (long-run) • Theoretical result: the long-run natural rate of unemployment does not depend on the level of productivity (nor on the rate of productivity growth) • Empirical reality: a positive relationship appears to be present between productivity growth and the level of long-run employment – See Fig.13.5 which indicates that in the US decades of higher productivity growth are associated with a lower unemployment rate (1940’s, 50’s and 60’s) and low productivity growth results in higher unemployment (1970’s and 80’s) Empirical Evidence (long-run) Figure 13 - 5 Productivity Growth and Unemployment— Averages by Decade, 1890 to 2000 There is little relation between the 10-year averages of productivity growth and the 10-year averages of the unemployment rate. If anything, higher productivity growth is associated with lower unemployment. Empirical Evidence (long-run) • Measurement issues: • Difficult to measure the natural rate of unemployment (as it is not observable) solution: use the actual average rate of unemployment over decades – this is a satisfactory approximation because the actual rate of unemployment moves around the natural rate • Measuring average productivity growth over a decade takes care of labour hoarding, as productivity gains due to increased use of existing labour may be significant in the short-run, changes in labour hoarding are unlikely to impact on productivity growth over a decade Empirical Evidence (long-run) • How does theory explain the inverse relationship between productivity growth (A) and unemployment (u)t i.e. high productivity growth (A) leads to lower natural rate of unemployment (u) • As follows: – It takes time for expectations to adjust to the reality of productivity growth – As a result in the context of a slow down in productivity growth - slow expectations adjustment means that workers keep asking for wage increases that are too high for the new lower rate of productivity growth (leading to lower levels of employment i.e. Au) – Or in reverse, if there is an increase in productivity growth, slow expectations adjustment means that workers do not upwardly adjust their salary increases (leading to higher levels of employment Au) Empirical Evidence (long-run) • If price expectations are correct (Pe = P) • But productivity expectations are NOT correct (Ae≠A) • Then the implied price-setting and wage setting relations are given by: W A Price setting: P 1 W A e F(u.z) P Wage setting: e • If productivity growth declines then A increases for some time by more than A (Ae>A) Empirical Evidence (long-run) • If (Ae>A) i.e. expectations adjust slowly to reduced productivity growth then the wage setting relation shifts up by more than the price setting relation (equilibrium shifts from B to B’ in Fig 13.6 resulting in an increase in the natural rate of unemployment from un to un’) • The natural rate of unemployment will remain high until expectations of productivity have adjusted to the new reality (where Ae=A) • Conclusion: after the slowdown in productivity growth workers ask for larger wage increases than firms are able to give, leading to a rise in unemployment. As expectations adjust unemployment will fall back to its original level. Empirical Evidence (long-run) Figure 13 - 6 The Effects of a Decrease in Productivity Growth on the Unemployment Rate When Expectations of Productivity Growth Adjust Slowly If it takes time for workers to adjust their expectations of productivity growth, a slowdown in productivity growth will lead to an increase in the natural rate for some time. Summary of findings (short-run and long-run) – In the short run, the response of employment to technological progress is ambiguous – increases in productivity sometimes decrease unemployment and sometimes increase unemployment. (See slide on the the US Jobless Recovery in early 2000’s) – In the medium to long-run, there is an inverse relation. Lower productivity growth leads to higher unemployment and higher productivity growth leads to lower unemployment. – So where do fears of technological unemployment come from? They must be based in structural change – the change in the structure of the economy induced by technological progress, a process which produces “winners and losers” The New Economy, the U.S. Expansion of the 1990s, and the Jobless Recovery of the Early 2000s By the end of 2001, the recession in the U.S. was over, and output growth was positive in 2002 and 2003. But unemployment continued to increase. The recovery was dubbed the jobless recovery. This was because output growth (Y) – in the context of high productivity growth (A) - was not sufficient to reduce unemployment N=Y/A). Output growth was stunted by the loss of confidence in the “new economy” which meant there was no boom in consumption or investment. Table 1 Selected U.S. Macroeconomic Variables, United States, 1996-2003 1996 1997 1998 1999 2000 2001 2002 2003 GDP growth (%) 3.6 4.4 4.2 4.4 3.7 0.5 2.2 3.1 Unemployment rate (%) 5.4 4.9 4.5 4.2 4.0 4.8 5.8 6.0 Inflation rate (GDP deflator, %) 1.9 1.9 1.1 1.4 2.2 2.4 1.5 1.7 Labor productivity (%) 1.8 2.2 2.2 2.4 2.6 0.7 3.9 3.4 3. Distribution effects and technological change Joseph Schumpeter characterised the process of growth as a process of creative destruction – new goods are developed, making old ones obsolete, new techniques of production are introduced. This is the process of structural change – a process that has distributional consequences – as some industries (and some people) are winners and others are losers Churning is another the term used to describe how new techniques of production require new skills and make old skills less useful. (Coined by Robert McTeer in his book “The Churn: The Paradox of Progress” (1993)) The Increase in Wage Inequality • For those in growing sectors (winning industries rising on the winds of new technology) – or those with the rights skills (skills appropriate to the new technologies) – technological progress leads to higher wages. But for those in declining sectors and with outdated skills – technological change means lower wages or even job loss. • As a result - technological change is the reason for the large increase in wage inequality in the United States during the last 25 years. In particular those with access to higher levels of education are able to access jobs in growing sectors and have appropriate skills for the new technology driving these sectors. (See Fig 13.7 which shows the evolution of wages in the US be education level form 1973 to 2005) – At the low end of the education ladder, both the relative and the absolute wage of workers has declined – At the high end, the relative wage of those with an advanced degree has increased by 25% since the early 1980s. The Increase in Wage Inequality Figure 13 - 7 Evolution of Relative Wages, by Education Level, 1973 to 2005 Since the early 1980s, the relative wages of workers with a low education level have fallen; the relative wages of workers with a high education level have risen. The Causes of Increased Wage Inequality • Wage inequality in the US is driven by the steady increase in demand for high skilled workers relative to low skilled workers (which is exacerbated by the fact that the growth in supply of skilled workers has failed to keep pace with the growth in demand) • This relative growth in relative demand for skilled workers is driven by: – International trade: Firms that hire low-skilled workers usually go abroad to find this source of labor (reducing demand for low skilled workers). – Skill-biased technological progress: New machines and productive methods require high-skill workers with better education (increasing demand for high skilled workers). (this trend is present across all sectors) Will wage inequality continue to steadily increase in the US? • The future may be different from the recent past where wage inequality is concerned: – The trend in relative demand may slow down. (as computers become easier to use and accessible by low skilled workers and replace high skilled workers) – Technological progress is not exogenous. R&D will be incentivised to lead to technology that is less skills biased to take advantage of low-skill low-wage workers – The relative supply of high-skill versus low-skill workers is not exogenous. There is a high incentive to gain skills but public policy must ensure adequate basic education and financial access to higher education. 4. Institutions and technological change For poor countries, technological progress is more a process of imitation than a process of innovation. But some developing countries (e.g. China) have succeeded in this process of stimulating technological progress, but others have failed (e.g. most African countries, such a Kenya where PPP adjusted GDP is 1/30th of the US and A is 1/15th the US level.) Why do poor countries (like Kenya) not adopt the technological knowledge that is readily available in the world and closing the technological gap that exists. Most economists believe that the main source of the problem, for poor countries in general lies in poor institutions. What institutions do economists have in mind? At a broad level, the protection of property rights may well be the most important. Few individuals are going to create firms, introduce new technologies, and invest, if they expect that profits will be either appropriated by the state, extracted in bribes by corrupt bureaucrats, or stolen by other people in the economy. (this argument risks being ahistorical as it neglects the damaging effects of imperialism and colonialism and the unfair establishment of property rights associated with colonialism, also there are geo-political factors eg island economies, landlocked economies, climate change) Institutions and output • Fig 13.8 shows a strong positive relationship between the degree of protection from expropriation (protection of property rights) and GDP per person across various countries from 1985 to 1995 • Findings: – low protection of property rights is associated with low GDP per person (e.g. Zaire and Haiti) – high protection of property rights is associated with high GDP per person (e.g. US, Norway) • See further examples of North vs. South Korea and effects of market-oriented reforms in China Institutions and technological change Figure 13 - 8 Protection from Expropriation and GDP per Person There is a strong positive relation between the degree of protection from expropriation and the level of GDP per person. The Importance of Institutions: North and South Korea 50 years after Korea was divided into two countries the GDP per person was 10 times higher in South Korea than in North Korea. This was the result of South Korea’s capitalist organization of the economy versus North Korea’s nationalized industries and centralized planning by the state. There were no private property rights for individuals. The result was the decline of the industrial sector and the collapse of agriculture. The lesson is sad but transparent: Institutions matter very much for growth. The Importance of Institutions: North and South Korea Figure 1 PPP GDP per Person,North and South Korea, 1950 to 1998 What Is Behind Chinese Growth? In 1978, an agricultural reform was put in place, allowing farmers, after satisfying a quota due to the state, to sell their production on rural markets. Outside of agriculture, state firms were given increasing autonomy over their production decisions, and market mechanisms and prices were introduced for an increasing number of goods. Private entrepreneurship was encouraged, often taking the form of “Town and Village Enterprises,” collective ventures guided by a profit motive. Tax advantages and special agreements were used to attract foreign investors. Despite poor establishment of property rights and an inefficient banking system China’s economy continues to grow. Conclusion • What types of institutions are important to fostering technological progress – Political system where state cannot expropriate property of citizens (highly politicised issue) – Good judicial system to resolve disputes between state and individual and between individuals – Laws against insider trading to promote confidence in the stock market – Clear and well enforced patent laws to promote R&D – Good anti-trust (competition) laws to protect competitive markets and avoid monopolies that have few incentives to introduce innovations • Conclusion – it is difficult to start the virtuous circle of higher GDP growth and better institutions, particularly as the causality runs both ways and low GDP leads to less protection form expropriation and makes the building of correct institutions (which are costly) more difficult