TUBOS DE SLIPLINING

Due to the fact that interdependence between output and the fiscal stance evolve quickly, quantitative analysis of data is hardly possible when aiming at understanding the impact of the recent financial crises on youth unemployment. The methodology of this paper is defined by applied research based on the theoretical implications indicators of financial crises and financial crises management have on youth unemployment and NEET rates in particular. Regarding the methodological approach of addressing NEET rates as a dependent variable of aggregate performance, namely output, the following equation by Blanchard et al. (2010) will be used in order to derive the output based on the following factors:

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Y= c0+ c1 (Y-T) + G + I

In this equation, output (Y) depends on private on private consumption, represented by c0(as the basic

level of private consumption in an economy) and c1(as the marginal propensity to consume, depending

on disposable income, which is derived from income (Y) minus taxes (T)). G is government spending while I is investment. In this paper, taxes will be left out of the focus and private consumption will be related to both regulatory indicators having an impact of private income, evolving from social benefits, such as pensions, minimum wages and the EPL index.

On the whole, output will serve as the explanatory factor on top, which is determined by private consumption, government spending and investment. This approach derives from the output dependency established by the existing literature, which derives from the dimensions further

identified. Moreover, private consumption is supposed to be influenced by spill-over effects evolving from investment and government consumption, for instance through the remuneration of civil servants. The fiscal, regulatory and investment dimension is supposed to be shaped by financial crisis and financial crisis management, most notably by the economic adjustment imposed by the Troika. Another spill-over effect evolves from changes of the three aforementioned subordinated dimensions on private consumption and the connection. The multi-layer approach used in this paper is therefore identified by output on top, defined by the equation of Blanchard et al. (2010), which is further determined by the explanatory factors of the dimensions identified, which again is shaped by financial crisis management.

Therefore, the indicators supposed to clarify the soaring NEET rates in the PIGS countries between 2006 and 2013 are defined by

- Economic performance (output): real GDP growth, real GDP/capita,

- Public financial dimension (fiscal angle): government consumption, government investment, - Private financial dimension (investment): hot capital (portfolio investment) vs. fixed capital

(FDI)

- Non-financial dimension (regulatory angle): labour cost (tax wedge, ratio of minimum wages to median wages), employment protection legislation (EPL), opportunity cost (net benefit replacement rates)

Ultimately, income related shifts evolving changes in both regulatory and public financial indicators, as government consumption also relates to private spending by public sector wages will be retrieved from consumer confidence index (CCI) levels in order to grasp the impact on private consumption, which is considered as critical in demand led economies. Due to the fact, that G concerns government spending which is composed by government consumption and government investment including government size and public sector wages, government transfers, such as pensions will be covered by the explanatory factors of the regulatory dimension. Therefore, the fiscal dimension has a direct impact on output, while its indirect impact is defined by private consumption, evolving from public sector wages and employment. The same indirect effect evolves from the impact of the regulatory dimension on private consumption. Finally, it will be critical to see whether changes in public sector wages and public employment translate into other CCI levels than regulatory shifts do. According to various economists, aggregate demand is a macroeconomic variable, which strongly correlates negatively with youth unemployment and accounts for fiscal policy changes, among others

government spending (Clark & Summers, 1982). Due to the critical role of aggregate demand during the recent period of financial crisis, household disposable income and household final consumption expenditure, in order to grasp whether CCI levels are based on a solid ground regarding the former and actually translate into consumer confidence regarding the latter.

When it comes to investment, the shock evolving from the GFC is expected to translate into lower investment levels in terms of hot and fixed capital and in lower private consumption as one of the direct consequences of the private credit crunch. It will be interesting to uncover the development the

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level of investment during the SDC and EZC as an indication of financial market confidence towards the PIGS countries.

The economic analysis will be conducted by a bottom-up approach using the multi-level framework described above. The policies will be linked to evolving values of indicators of the three

aforementioned dimensions, which will then be linked to the resulting outcome in output and then to the cyclically following NEET rate in the next year. Further, the direct impact of fiscal, private consumption and investment on output will be discussed, thereby determining which changes have had the biggest impact on output and which changes this reflects regarding their own values. This will lead to conclusions on their effectiveness when explaining NEET rates and towards statements about the dialectic of financial crises and financial crises management with NEET rates as the final outcome of their impact.

In order to draw conclusions on the evolving impact on NEET rates based on the data considered, the national and Troika based policies will be taken into account when analysing movements. This will lead to a comparison between the impact of indicators on NEET rates among the different periods and policies in order to answer the RQ and the SQs. Moreover, it will lead to an evaluation of the

interaction of the Troika with the national profiles in terms of economic success regarding NEET rates. Finally, this will be compared among the PIGS countries.

The data collection is of secondary nature, as data has been collected from OECD, Eurostat and the World Bank. Hereunder, the dimensions, explanatory factors and their indicators will be lined out in terms of operationalisation and definitions.

Defining the indicators

Aggregated performance will be operationalised by output, which is supposed to explain the super- cyclical character of YUR and NEET rates in particular (Khramrov & Lee, 2012; Freeman & Wise, 1982). Defining output is most commonly done by real GDP (Ball et al., 2013). Output will be operationalised by real GDP growth rates, which is often used to measure the applicability of Okun’s law (Banerji et al., 2015). Data on real GDP growth rates will be retrieved from the OECD statistics website. The real GDP growth rate is defined by the annual changes in gross value of final goods and services minus the value of imports measured at constant prices (OECD Data, 2016).

The dimension of aggregate performance is one of the most important features of financial crises and will be measures by the explanatory factors of output. According to Blanchard et al. (2010) and a variety of other economists, the recently witnessed period of financial crisis implied as an aggregate demand shock to aggregate performance, which underlines the value of integrating CCI, HDI and HCE levels into the analysis. CCI levels’ definition derives from households' plans for major

purchases and their economic situation, both currently and their expectations for the immediate future. Opinions compared to a ‘normal’ state are collected and the difference between positive and negative answers provides a qualitative index on economic conditions (OECD, 2016g). Moreover, HDI is defined by sum of wages and salaries, mixed income, net property income, net current transfers and social benefits other than social transfers in kind, less taxes on income and wealth and social security contributions paid by employees, the self-employed and the unemployed (OECD, 2016). The indicator of HFCE is defined by the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households, as a share of GDP (World Bank, 2016).

This approach derives from the fact that both output and household disposable income have witnessed harsh declined during the aforementioned period of financial crises, starting with the GFC in 2008. The GFC has been the origin of the credit crunch phenomenon as a whole, causing both output and HDI to fall drastically in most Western economies. Output shocks will be measured by real GDP

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growth rates measuring output performance change over years based on the development of price levels. Data on real GDP growth rates will be retrieved from the OECD, the same holding for HDI levels.

The layer in between characterised by CCI levels is expected to have enormous volatility as well during the period of recent financial crises due to private consumption expenditure. CCI levels function as a layer in between in this research as it captures domestic demand levels as version of aggregate demand in a way that combines private consumption climate and government consumption, allowing one to make statements about the plans of consumers of the PIGS countries, due to the critical importance of domestic demand levels in the PIGS countries. Moreover, CCI levels are able to connect indicators of financial crisis management and output shocks as the ultimate explanation for higher NEET rates.

The private financial dimension and its developments forms the second important feature of the GFC and is conceptualised by the explanatory factor of investment. Investment points at the relevance of hot and fixed capital. The former concerns portfolio investment while fixed capital is defined by long- term interest of which Foreign Direct Investment (FDI) is an example. FDI is supposed to be clearly linked to enhanced economic growth and higher employment (Ramirez, 2006). Driffields & Taylor (2000) point at the generation of high-skilled employment and the reduction of structural

unemployment by higher FDI.

As said before, the GFC forms the very origin of the credit crunch phenomenon that characterises the recent period of financial crises, which means that investment is meant to signify the outrages

consequences of the GFC in forms of declining transnational financing of the private sector. Thus, the investment angle is operationalised by the relevance of FDI and FPI in the PIGS countries. In this sense, the comparison of the relevance and of the development of both indicators is able to determine financial market confidence to a certain extent. Moreover, investment directly determines output according to Blanchard et al. (2010) and therefore indirectly explains NEET rates. Data on FDI and on FPI are retrieved from the World Bank data base (2016). FDI is defined by the net inflows of

investment to acquire a lasting management interest (ten per cent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital and short-term capital and short-term capital as shown in the balance of payments. FDI is measured as a percentage of GDP. FPI on the other hand is defined by portfolio equity net inflows from equity securities other than those recorded as direct investment and including shares, depository receipts and direct purchases in stock markets by foreign investors, measured by current US-Dollar prices (World Bank, 2016). As already stated during the theoretical framework, investment and unemployment highly correlate, with the level of investment and absorption capacity being highly defined by characteristics national profiles. Therefore, the investment angle has a direct impact on output, which then determines the level of NEET rates. The fiscal angle will be operationalised by government consumption and gross fixed capital formation, with the latter being appropriate in order to measure government investment (Financial Times,

2016a). General government final consumption expenditure covers government purchases of final goods and services produced by the economy and compensations of public employees, which includes government size and public wages. Gross fixed capital formation is composed by the investment in public infrastructure including public transport, health and education. Data on both indicators are measured as a percentage of GDP and are provided by the World Bank (2016a).

Coming to the dimensions of financial crises management, the public finances and regulatory dimension have been highly addressed by the Troika and to a diverging extent, by national

governments of the PIGS. It is of very high importance that public finances, being conceptualised by the explanatory factor of the fiscal angle, which translates into the operationalisation of indicators concerning government spending are able to determine output significantly, according to Blanchard et al. (2010). Especially in demand led economies, public spending to enhance the latter serves as an

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increasing factor of output. Therefore, gross fixed capital formation as an indicator for government investment, being defined by infrastructural construction in terms of transport, education and health service facilities, is able to enhance demand for labour by increasing output. The same holds for general government final consumption expenditure, which the World Bank (2016) classifies by public expenses towards purchasing of goods and services including public sector employees and their wages. In countries that highly depend on the public sector state-owned enterprises, general government final consumption expenditure is an important determinant of domestic demand. Therefore, the public financial dimension is supposed to have the same output-directed impact on NEET rates as investment, depending on the characteristics of the national profiles. Moreover, it is supposed to have a direct impact on HDI and an indirect impact on CCI levels, due to the inclusion of public sector wages. Both indictors of the public financial dimension are measured as a percentage of GDP.

Regarding the regulatory dimension, the indicators supposed to represent the explanatory factors of employment protection, labour cost and welfare state generosity most sufficiently, are supposed to be EPL, the tax wedge defined by total labour cost minus wages, minimum wages relative to median wages and by opportunity cost, which is measuring earnings while having worked versus earnings while being unemployed. Additionally, pension spending will be covered by the regulatory dimension due to its relevance regarding private income and private consumption.

The regulatory dimension evolved from financial crisis management as it mostly covers the aspect devaluation, while the public financial dimension most importantly covered austerity measures. Nonetheless, the expenditure on pensions and on public transfers are incorporated in the regulatory dimension, due to the conceptualisation of regulatory factors, being opportunity cost, labour cost and EPL (Blanchard et al., 2010). The indicators of the regulatory dimension are supposed to be shaped by financial crisis management policies, most of all internal devaluation. Subsequently, the regulatory changes are supposed to have an impact on private consumption, which is supposed to explain changes in output, next to the fiscal and investment related dimension. Further, opportunity cost are

operationalised by net benefit replacement rates, being the difference between net income from work of average workers earning 100 per cent of average wages and the unemployment benefits probably earned in case of unemployment. Thereby, net benefit replacement rates cover indirectly social transfers in terms of unemployment benefits and translate the institutional signalling of incentives to work or not to work (Eurostat, 2016). Depending in the relation between income from work or from unemployment, different signals may evolve when comparing countries and years. Data on

opportunity cost are retrieved from the Eurostat website. According to Blanchard (2010), government transfers, which social spending, such as pensions and unemployment benefits indicators actually are, do not add up to government spending when it comes to the composition of output. Nonetheless, opportunity cost have an indirect impact on output by private consumption levels, which are translated into levels of CCI and disposable income, determining private consumption and the multiplying impact of income from employment or social transfers, especially in demand led economies. When it comes to labour cost, this explanatory factor is operationalised by tax wedge and minimum wages relative to median wages. The tax wedge is defined by proportional difference between total cost per employee in terms of taxes and social security contributions and net earnings from employment. Thereby it effectively measures the cost implied to employers and the benefits implied to employees, which makes the tax wedge a suitable measures for incentives to expand employment and to work, due to the impact of income taxes and social security contributions. Data on the tax wedge are retrieved from Eurostat (2016). As low tax wedges are supposed to increase the incentives to employment, this impact will be critically analysed regarding its effectiveness, being highly dependent on the national profile. Moreover, labour cost will be measured by minimum wages relative to median wages, which are further characterised by the level of minimum wages average meaning median wages of an economy. If minimum wages increase their share of median wages of an economy, this means that declining median wages harm private domestic demand by lower HDI and CCI levels, which is meant to result in lower output levels in demand depending economies. On the other side, if minimum wages

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are changed, this would have a reverse impact, which requires subsequent analysis of HDI and CCI levels, in order to grasp the general movements in wage levels in the labour market. Data on the relation between minimum and median wages will be retrieved from OECD data website. The last indicator of the regulatory dimension will be EPL, measured by the EPL index. This indicator might have the most direct impact on NEET rates, due to its definition of measuring the strictness of employment regulation in terms of barriers to dismissals and labour market segmentation. As a segmented labour market is a future of modern labour markets anyway, movements in EPL have important implications for young adults, which typically have a high share of temporary contracts and being more vulnerable to unemployment. Therefore, the impact of EPL shifts can be very well compared to shifts in adult unemployment rates, in order to grasp the difference in impact in the already more vulnerable young adults being more frequently employed in temporary contracts and on adults which are more likely to have fixed contracts. Data will be retrieved from the OECD EPL index, which is defined by synthetic indicators of the strictness of regulation on dismissals and the use of temporary contracts (OECD stats, 2016).

The economic analysis will be conducted by a bottom-up approach using the multi-level framework of the theoretical considerations in the following way. The policies will be linked to evolving values of indicators and their net of impact among each other, translating from policy changes into changes in