the relationship between real wages and labour productivity in Italy

Macroeconomics

Table of Contents

Introduction

Overview

Labour

Education

Technology

Investment level

Real Wages

Conclusion – Group (100 words)

Appendices

Appendix 1

Reference list

Italy is the 3rd-biggest national economy in the Eurozone and the 8th largest by nominal GDP in the world, (ref.). Italy is a founding member of the European Union, the Eurozone, the OECD, the G7 and the G20 (ref.). It is a large manufacturer and an exporter of a significant variety of products including machinery, vehicles, pharmaceuticals, furniture, food, clothing, and robots (ref.). However, the country’s economy has been struggling compared to other OECD countries in recent times see figure 1.

Figure 1: Real GDP per capita, average growth rate (Atlas 2018)

From 1998 to 2007 both wages and productivity were increasing. After 2007, GDP fell which coincided with wage stagnation and reduction in labour productivity, see figure 1. This study will examine that relationship and try to understand what factors affected it.

Figure 2, Source: Created by the authors using OECD, (2018) data

The study will take in account any policies or changes made by the Italian government over the past twenty years to explain relevant trends in the relationship. The explanation will be supported using any relevant, assumptions, theories and models to help illustrate the points made.

In terms of definitions, ‘Real wages’ is the average wage per capita and ‘Productivity’ can be expressed by the following equation where Productivity is equal to Total Factor Probability (Q), Q = f (L + K) x T where L = labour, K = Capital invested and T = Technology. This concept is essential in macroeconomics to describe an economy’s supply capability: Yt = f (Lt, Kt) At. Where the technology factor is often referred to as the unassigned input to the total factor productivity (TFP) equation. In the short term, K and A are fixed, but in long term these factors are variable. (ref book)

Taking Labour Productivity first. This breaks down into three factors, Labour, Capital and Technology. By looking at what factors can affect Labour productivity then we can ascertain the drivers behind the graph.

Labour

In 1997 (Treu package) and in 2003 (Biagi law) the government introduced these reforms. The aim of these reforms was to boost employment and productivity by relaxing the rules around short term (temporary) contracts and introducing new non-standard employment contracts. This made it easier for companies to hire new workers, especially young people with no experience. This resulted in strong growth in employment in 1997, 2008 and 2014 but failed to address the rules on existing long-term contracts. Temporary contracts have a role to play in an economy but can be associated with low access to training and weak career progression. This results in negative implications for productivity and an increase in labour market volatility (REF). Temporary contracts can facilitate entry in the labour market after education, but may not help improve skill matching, before locking employees into a long-term arrangement. Excessive use of temporary contracts may also give rise to negative economic and social implications and include lower job tenure, less experience acquired on the job, limited access to training and social security, and lower wages. The larger the asymmetry between employment protection legislation for temporary vs. permanent contracts, the higher the possibility that temporary contracts become a trap, rather than a stepping stone toward quality employment (OECD, 2016). Such segmentation may have macroeconomic implications too, such as lower productivity (Blanchard and Landier, 2002; Garibaldi and Taddei, 2013; Damiani et al, 2016) and higher employment volatility (Bentolila et al, 2012). In the specific case of Italy, the literature cites the 1990s reforms of the labour market as one of the root causes for the productivity slowdown that characterised the second half decline of the decade. According to this literature, by the introduction of more flexible part-time and fixed terms contracts, into the labour market this resulted in less productive workers and reduced the incentives to invest in firm-specific human capital, for both employers and employees (see also Sestito, 2002; Garibaldi and Taddei, 2013; Daveri and Parisi, 2015). At the same time, by maintaining the strict regulation of permanent contracts, it continued to hinder turnover and made the economy more vulnerable to external shocks due to the rapidly changing employment patterns /levels. In 2013 the employment protection legislation for permanent contracts in Italy was more restrictive than in France and Germany, according to OECD indicators.

Get Help With Your Essay
If you need assistance with writing your essay, our professional essay writing service is here to help!
Essay Writing Service

Following the Jobs Act, Italy’s employment protection legislation was made less restrictive than in France and Germany, according to OECD indicators. The uncertainty that made dismissals very costly under the previous legislation was substantially reduced. The main objective of the reform was to improve reallocation and reduce segmentation; the latter has been supported by generous hiring incentives. The structural problems of the Italian labour market clearly impacted their labour productivity. Furthermore, short-term contracts result in poor training on the job and reduce the potential to produce higher skilled jobs which in turn would help increase labour productivity.  Poor foundational and higher education led to poor labour productivity. This is discussed further in the next section.

Education

Labour competency requires a threshold of knowledge or education level to produce the skills needed to have an effective and productive workforce (Oecd.org, 2018). Italy’s educational system does not create that environment nor produce these skills. The La Buona Scuola enacted legislation in 2015 to change this (Cedefop, 2018). However, because of years of poor government funding on education, as a consequence of an unstable political system, resulted in inconsistent and poorly implemented educational policies (45 different governments and 30 different education ministers since 1948 Cedefop, 2018). Investment in graduates and tertiary education (see Figure 5) fell and thus reduced the pipeline of new talent coming through the educational system to improve Italy’s economy.

Figure 5 shows Italy’s spending on tertiary education compared with other countries.

 Source: worldbank.org, 2018

 When a government does not invest in higher education it is an issue, but when a government does not invest in the right skills too, it becomes a massive issue. It is well known that investment in STEM/ICT skills training contribute directly to productivity and GDP improvement (Adda & Monti, 2017). In Italy only 7% of Italian Graduates were trained in STEM and ICT subjects and on average 15% of young people didn’t see the value of education and dropped out of university (Statista, 2018). 

This course of action taken by the government directly, impacts labour productivity, as found by Kampelmann et al. (2018) who stated that having higher educational credentials has a strong impact on increasing productivity. In addition, it contributes to a company’s profitability as when lower educated workers are substituted by higher educated ones. This effect is found to be more pronounced among younger workers too (particularly the white collar segment of the workforce) (Kampelmann et al.,2018).

Italy’s educational system is failing to equip its workforce both young and old with the required skills for the future.  It is not only confined to a mis-match for under-skilling, it is also found to be in over-skilling too. Globalisation and technological advancement are shaping the future for all countries around the world and helping them to transition from outdated traditional industry to more advanced ICT focused industries. This is the key to improving future productivity and GDP growth. Without a successful transition, Italy may find itself stuck in a low economic development sector.

Find Out How UKEssays.com Can Help You!
Our academic experts are ready and waiting to assist with any writing project you may have. From simple essay plans, through to full dissertations, you can guarantee we have a service perfectly matched to your needs.
View our services

A skills mis-matched labour force, an inefficient education system focus on STEM/ICT and a high concentration of SME’s (which doesn’t demand such high skill professionals), together with its focus on tourism and retail sector, further distorts Italy’s work force profile and has contributed in Italy’s inability to improve its productivity and recover from the past financial crisis compared with other OECD countries.

It is not surprising that having a large mis-match in skills vs job requirements has led to higher unemployment too. Further exacerbating labour productivity See figure

Figure 4: Unemployment rate, percentage

Source: Italian national institute of statistics, measure in percent)

Technology

Technology as a factor in labour productivity can be expressed as Total factor Productivity (TFP). TFP is measures in broad terms of technology impact. The Cobb-Douglas equation described shows the relationship between Labour, Capital and Technology. In figure xx below for Italy the Technology factor (TFP) is decreasing.

Figure XX: Italy TFP Growth Breakdown (EU KLEMS 2018).

The Technology factor can be broken down into two main parts, ICT and R&D (Edquist & Henrekson, 2017). Use of technology or the knowledge gained from R&D can be used to increase process efficiency and product quality (OECD, 2003) and therefore is one of the main drivers of productivity acceleration’ (Van Ark, O’Mahony, and Timmer, 2008). In Italy’s case it can be postulated that Italian productivity has levelled off because of low ICT investment and application.

Figure XX: Share of ICT investment in non-residential fixed capital formation (Hassan and Ottaviano 2013)

Bloom, Sadun, and Van Reenen (2012) cite that practices of management have a high impact on ICT penetration and exploitation, they cite that Italian management tends to:

Figure xx: Italian management trends (Bloom, Sadun and Van Reenen 2012)

Bloom, Sadun and Van Reenan (2012) looked at Italy compared to France and Germany in relation to ICT 9investment using the measure ‘Computers per employee’, Italy scored the lowest. Conversely, Italian sectors that had embraced Technology, were on average more productive (Landi & Landi, 2017). Furthermore, sectors that embraced technology were less likely to be affected by labour and capital changes and be more robust during financial downturns. (Landi & Landi, 2017).

Italy clearly, have issues relating to management and technology adoption. This is further exacerbated as their R & D and innovation investment levels are falling too. (European Commission, 2014). R&D spend in 2013 was 0.68% of GDP compared with 1.61% in OECD countries. Triadic applications were 1.4% compared with 4.9% and 10.8% for France and Germany (European Commission, 2014). Continued lack of investment in these areas will reduce productivity, impact real wages and therefore growth.

Investment level

Labour productivity depends on how much capital is available to invest per worker. Investment isn’t high in Italy, figures  xx and xxx below. This might explain the decrease in productivity following the Financial crisis 2007/8.  In addition, high debt levels may also explain why Italy’s investment in capital/tech levels are relatively low too as a large part of Italy’s GDP is used to pay interest on their debt.

Figure xx: Private equity investment 2014 (Pinelli et al., 2015)

Figure xx: Venture capital investment 2014 (Pinelli et al., 2015)

Economic stagnation in the last twenty years reflects the low labour productivity growth in Italy. A slowdown in total factor productivity along with a reduction in investment, are contributing to the poor labour productivity growth (OECD 2018).

Italy’s fiscal policy has been a fine balance between deficit reduction and sustainable growth. In that the central Italia government has been committed to create the fiscal space for growth policies by reducing the interest payments. After the credit crunch, payment to public debt have reduced from an estimated 6% in 2012 to 4.5% in 2016.

Fiscal space allows the government to redirect spending on public investment, which has been the priority since the start of the crisis. The public spending on education, general public services and housing and community amenities has been at its lowest point in the last 20 years. These are part of the structural root causes behind the slow growth on productivity. Reliance on low productivity sectors, inefficient public administration and ineffective regulation around small and medium sized firm’s growth are only a few of the structural issues highlighted in literature (ref productivity growth, wage growth and unions ECB).

Looking into the business environment, before the crisis the rise of firms with persistent problems meeting interest payment had adverse effects in sinking the business investment. This reduced the aggregate labour productivity as “zombie firms” fed from investment opportunities that more productive companies had, discouraging innovation (Adalet McGowan et al, 2017). During and post crisis equity-share sales to foreign investors is discouraged by inheritance tax exemptions on the families controlling the stakes of SMEs in Italy.

Being a primary family owned market, Italy has a large percentage of family owned businesses solely managed by family members. The risk averseness of such SME is the primary reason behind the low private R&D spending and technology adoption. Additionally, limited non-bank sources of private finance is constraining innovative SME from growing. Away from bank loans, an underdeveloped stock exchange market is hindering risk taking and innovation preventing start-ups from entering the market and obstructing the reallocation of resources from least productive firms to more productive.

Real wages have stagnated from 2007 to 2018. In fact, you could say that they have been kept artificially high. It may be expected that if labour productivity falls, like it has then real wages should mirror it. From 1998 to 2007 real wages and labour productivity curves were almost identical suggesting a direct relationship. Following the financial crisis, the Italian government (EU) could not allow wages to fall in real terms or their population would be in dire poverty. Therefore. they had to cut back on other things, like higher education, technology and R & D whilst making sure they paid off their national debt.

Real wages and labour productivity should have a direct link. For Italy from 1998 to 2007 this held true. However, from 2007 to 2018 there appeared to be no link. However, as labour productivity is directly linked to educational, capital and technology investment, we know these were ‘cut back’ in the latter decade to bolster up real wages. However, the down side of this policy was that the government lack of investment has led to skill mismatches, poor innovation (low R&D investment) and labour volatility due to short term contracts which has resulted in slower growth than other OECD countries.

Bloom, N., Sadun, R. and Reenen, J. (2012). Americans Do IT Better: US Multinationals and the Productivity Miracle. American Economic Review, 102(1), pp.167-201.

Edquist, H., Henrekson, M. (2017) ‘Do R&D and ICT affect total factor productivity growth differently?’ Telecommun, Policy, 41 (2), pp. 106-119

European Commission, (2014) “In-depth review of the Italian economy”, European Economy Occasional Papers, No. 182, 2014

Kampelmann, S., Rycx, F., Saks, Y., Tojerow, I. (2018) ‘Does education raise productivity and wages equally? The moderating role of age and gender.’ IZA Journal of Labor Economics, 7(1), 1.

Hassan, F., & Ottaviano, G. I. P.  (2013) ‘Productivity in Italy: The great unlearning’, VoxEu.org, 30 November.

Landi, N., (2017). ‘Sector technology advancement as driver of Italian total factor productivity’, Jan 2017

OECD, (2003) ‘Seizing the benefits of ICT in a digital economy’ OECD, Paris

Pellegrino, B., Zingales, L. (2014) ‘Diagnosing the Italian Disease’, Working paper, University of Chicago.

Pellegrino, B. and Zingales, L. (2017). “Diagnosing the Italian Disease.” SSRN Electronic Journal.

van Ark, B., O’Mahony, M. and Timmer, M. (2008). The Productivity Gap between Europe and the United States: Trends and Causes. Journal of Economic Perspectives, 22(1), pp.25-44.

World Economic Forum (2015), ‘Global competitiveness ranking’, http://reports.weforum.org/global-competitiveness-report-2015-2016/competitiveness-rankings/#indicatorId=GCI.B.08.01.

Medium, (2018) ‘No Net Change in Italian Living Standards Since the Introduction of the Euro.’ [online] Available at: https://medium.com/@NoahCarl/stagnation-in-italian-living-standards-since-the-introduction-of-the-euro-44956d3035c4 [Accessed 7 Dec. 2018].

Cedefop, (2018) ‘Italy – education reform.’ [online] Available at: http://www.cedefop.europa.eu/en/news-and-press/news/italy-education-reform [Accessed 7 Dec. 2018].

Statista, (2018) ‘Share of school leavers in Italy in 2010-2017’ | Statistic. [online] Available at: https://www.statista.com/statistics/776925/share-of-school-leavers-in-italy/ [Accessed 7 Dec. 2018].

theOECD. (2018) ‘Earnings and wages – Average wages – OECD Data.’ [online] Available at: https://data.oecd.org/earnwage/average-wages.htm [Accessed 7 Dec. 2018].

Data.worldbank.org. (2018). ‘Government expenditure on education, total (% of government expenditure)’ | Data. [online] Available at: https://data.worldbank.org/indicator/SE.XPD.TOTL.GB.ZS?locations=IT [Accessed 7 Dec. 2018].

Adda, J., Monti, P. (2017) ‘Unemployment and Skill Mismatch in the Italian Labor Market.’ [ebook] Bocconi-IGIER JP Morgen. Available at: https://www.unibocconi.eu/wps/wcm/connect/3e05b460-33aa-402a-b1ec-ccc795da190b/int_report_JPMorgan_MAIL+%281%29+%282%29.pdf?MOD=AJPERES&CVID=lRfKgSx&CVID=lRfKgSx&CVID=lRfKgSx&CVID=lRfKgSx&CVID=lRfKgSx&CVID=lRfKgSx [Accessed 7 Dec. 2018].