Ecomod 2014, International Conference on Economic Modeling, Bali, Indonesia

Evaluation of the potential of green and decent employment creation in Tunisia

Ulrike Lehr1, Andreas Bockermann, Anke Mönnig, Rafik Missaoui, Sami Marrouki, Ghazi Ben Salem

1 Gesellschaft für Wirtschaftliche Strukturforschung mbH, Osnabrück, Germany

Corresponding author. Tel: +4954140933280, Fax: +4954140933110, E-mail:

Abstract:

The paper suggests a methodology extend the IO table to exhibit green sectors. The contribution is based on a study commissioned by the ILO on the potential of green and decent job creation in Tunisia. The methodology further comprises a small model of the Tunisian economy to calculate green employment under different future scenarios.

Keywords:Green jobs, Input-Output-Analysis, Developing countries, MENA region

1.Introduction

Degradation of the environment, including the pollution of water, soil and air, the irreversible loss of biodiversity, and depletion of natural resources are global threats to sustainable development. Thethreats are enhanced by the impact of climate change already being felt in many developing countries. These challenges have led to the postulate of making the way we produce, work and travel more compatible with the ecological limits and boundaries of our planet. On the social level, the challenges of large unemployment especially among young people, the questions of inclusion and participation of the population in a better, healthier and safer life seem equally unresolved in large parts of the world. Under the headline of Green Economy,[1] suggestions have been made in the course of the RIO+20 conference on the question how these challenges can be addressed by a harmonized approach.

Currently, this is being translated into practice[2]. To develop the respective policies, legislation and support mechanisms, a rigorous framework of evaluation has to be established. The analysis of the status of green and decent employment and of the potential for the creation of green and decent jobs in the future is a necessary first on the pathway to a green economy.

The International Labor Organization (ILO) supports a series of studies in an attempt to develop a method for the measurement of green and decent employment. This paper deals with a study of this series, which evaluates green employment in Tunisia. For Tunisia after the Revolution of 14 January 2011, the targets of a transition to a green economy overlap with some of the most pressing needs and challenges the country is facing with respect to economic, environmental and social changes.

This paper summarizes the results. Itis organized as follows. The next section explains our approach and chapter 3 introduces the scenarios for the future development of renewable energy and energy efficiency. The scenarios are given in terms of capacities installed, investment necessary, import quota assumed and export levels. Section 4 explains the main drivers of employment from renewable energy and energy efficiency increases and puts a perspective on the results that can possibly be expected from the experience in other countries. Section 6 gives results and Section 7 concludes.

2.Methodology

The applied methodology consists of three steps: in the first step, a “green input-output (IO) table is created, which is consistent with the existing IO data from the Tunisian Statistical Office (INS). The second step then yields the existing green jobs in the Tunisian economy as of yet from the application of IO analysis with the newly designed IO tables. Step 3 comprises the development a small GDP driven model with the time series of IO tables at its core and its application to scenarios for future green development.

2.1.Green extension of Input Output Tables – why?

Economic sectors produce goods and services for other sectors and for final consumption and, at the same time, use other goods and services to be able to produce their own goods and services. The idea of grouping these kind of input-output flows in a systematic and symmetric table goes back to Wassily Leontief, who won the Nobel Prize in economics in 1923.

Input-output tables provide information about the production and consumption of intermediate and final goods. Input-output tables capture the circulation of products within an economy for a given period. They condense the complexity of economic action with all its effects, counter-effects, actions and re-actions.

Theyare the tool of choice for the type of analysis discussed in this paper, because they facilitate the understanding of structural changes, which occur in the wake of “greening” of the Tunisian economy. Following the Interagency[3] Workshop on Employment and Social Inclusion in a Green Economy (ITC 2013) suggestion, input-output (IO) analysis (together with SAM based modeling) “can be used to estimate the effects on employment resulting from the increase in final demand for the product or service in a given green industry by estimating direct, indirect and induced jobs. Thus, the model can be used to answer questions such as “How many jobs may result from a given program of investment in sustainable economic areas?” or “For a given level of investment, which sector or sectors would yield the greatest number of jobs?” “(ITC 2013).

To the green jobs analysis, IO tables can contribute when we split each sector into its green and conventional part and apply the Leontief inverse. X denotes total output by sector; I is the identity matrix, A is the green IO matrix, y denotes final demand and m denotes imports.

[1]

Based on this equation, production-induced employment effects result from standard input-output analysis (Holub & Schnabl 1994[4]). To this end, the Leontief inverse needs to be left multiplied with a diagonal matrix of employment coefficients (b) the resulting matrix can be interpreted as a labor input matrix W.

[2]

IO calculations are relevant for the analysis of green jobs in a country, because it gives a relation between green outputs (which still needs to be clearly defined) and the sector specific production structure of the country. An example for this is additional demand for organic agricultural produce due to a campaign or a subsidy. This additional demand directly translates into additional production, assuming that the additional amount will not be imported completely. Additional productionrequires additional workers, in sowing, watering and harvesting in the case of crops. This employment effect is often called direct employment in the literature. From the IO table, we can further read the additional demand for intermediary inputs. All respective sectors will have additional demand for labor and thus yield additional employment. This effect is often called the indirect employment effect. In the agriculture sector,for example this effect could extend to the machinery sector, the construction sector, transport and trade.

2.2.Green extension – how?

We aim at the extension of the Tunisian IO table to account for green economic activities. For this, we split each column and row of the IO table into their green and conventional parts. To be able to do this consistently, i.e. to leave the sums over the rows and columns unchanged, we developed a set of construction rules. We have to define the share of green output per sector, the input structure of production and the delivery of intermediate goods of the green and conventional part of a sector to other sectors (Figure 1).

The share of green and conventional production follows the literature and expert interviews. The information is scattered, but data on green production exist for Tunisia. It turns out that some sectors can be fully considered as green, i.e. all of their output and all of their economic activities are considered as relevant for green jobs. Other sectors cannot be considered as even partly green. Most sectors have some green production.

More difficult to determine and with no data available is the delivery of green intermediate inputs. This can be seen as green products used in conventional production or conventional products used in green production or green used in green. To facilitate the construction, we defined all inputs to green sectors as green. This includes e.g. metal construction for solar panels as well as organic inputs to organic agriculture.

The input structure of other sectors to production also is very difficult to determine for all sectors from existing data. Therefore, we set the input structure into green parts equal to the conventional structure – unless we know otherwise. In Lehr et al. 2014, the only exception is agriculture (see discussion below).-

Figure 1: Illustration of the split of sector i.

Box 1 summarizes the set of construction rules for the green IO table for Tunisia.

Box 1: Construction rules

Rule 1:Sectors differ in their green shares between 100% and 0%.

Rule 2:Inputs to green sectors are green.

Rule 3:The input structure of green sub-sectors is the same as of their conventional counterparts.

Rule 4:Exceptions to Rule 3 have to be separately identified.

Rule 5:Zero percent green sectors are an exception to rule 3 as well; their inputs to green sectors do not create a green production in the sector.

Technically, the rule set identifies a transition matrix with twice as many rows and columns as the original IO matrix. Multiplication of the transition matrix with a hypothetical matrix where all rows and columns are duplicated yields the final extended IO matrix.

2.3.Which sectors are green? Which products are green?

To determine the green shares of production and services for Tunisia, two stakeholder workshops contributed. The discussion yielded that the waste and water sector is 100% green, organic agriculture should claim significant shares in the future and the Tunisian Solar Plan would contribute to green jobs.

  • The waste and water sector in Tunisia

Waste collection and treatment as well as water collection, distribution and treatment improve the health, the environment and protect nature and the Tunisian citizens. Therefore, these sectors can be considered green. The question, which was intensively discussed on the workshop, is if the jobs in these sectors are decent, too. Only when the latter criterion is fulfilled, a job can be called green by ILO standard. The legislator framework for ensuring workers’ rights and forbidding child labor in micro enterprises such as waste pickers are in place in Tunisia. Though they may not be fulfilled to the last jota, especially under current circumstances, this mostly takes place on informal labor markets. The statistical data we work with in this exercise refer to the official labor statistics.

  • The Tunisian Solar Plan

Employment effects from the Tunisian Solar Plan had been analyzed by the authors in a preceding study. They were found to be positive and dependent on the technology mix and the level of domestic production and integration. The results here are similar.

  • Organic agriculture

The movement of organic farming in Tunisia started in the 80s by private initiatives and had a slow development until 1997-1998.Then, a national strategy has been implemented and is based on several components: regulation, research, training, extension, organization, structure and encouragement. This has contributed to the development and growth in this sector.

Tunisia relies heavily on farming. Organic farming becomes increasingly important, also driven by the expectation of opening new export opportunities. With 330,000 hectares certified organic by the end of 2013, it is the second largest area of organic farming in Africa. Tunisia became the largest producer of organic olive oil.The Technical Centre for Organic Agriculture (CTAB) was established under Law No. 96-04 of 19 January 1996 on technical centers in the agricultural sector and under the Order of the Ministry of Agriculture 2 October 1999 on the establishment of CTAB.

The area of organic farmland is estimated at 245,000 hectares at the end of 2011 and projected to reach 500,000 hectares in 2016. Organic olive groves represent 47% of total current area of organic farmland followed by organic pastures (18%) and aromatic and medicinal plants (15 %).

3.Projecting green employment under different scenarios – the model

3.1.E4.tn

Basically, e4.tn is constructed top-down which means that the initial driver of the projection depends on the exogenous given GDP forecast until 2030. By applying constant shares, domestic final demand by 46 sectors grows each year with the same factor as total GDP. In the baseline scenario, green final demand grows in accordance to its conventional counterparts.

Baseline GDP growth rates have been developed based upon targets from the Tunisian government. Given the current situation of economic development – 2013 showed a growth rate of 2.5% - they might seem optimistic. However, with the constitution adopted and institutional changes settling, economics c will pick up speed in the near future.

The Leontief production function gives the corresponding production, which is necessary to satisfy demand. Generally, the Leontief production function assumes a fixed proportion of input factors, which means that technological change is limited. By making input coefficients time dependent, technological change can be integrated in the model. In e4.tn, the input coefficients of the ten largest production sectors are extrapolated by applying a simple trend forecast. The results are shown in the following set of figures. An increasing input coefficient implies that more inputs are needed to produce the same amount of products. A declining input coefficient, vice versa, indicates that less inputs are needed for the same production amount. For instance, the food processing industry shows a declining input demand of agricultural products. Reasons can be manifold – for instance more efficient machineries or equipment are used for production which lowers the amount of “lost” inputs.

3.2.Final demand

Apart from the break-down of intermediate demand and supply to environmental goods and services, three further assumptions were necessary to embed green products in an input output context: the distribution of environmental goods and services on final demand, the production share of these goods as well as price developments for green products.

What is final demand for the green goods? For organic produce this is easily pictured, final demand comes from the consumer who wants to buy organic products. In Europe, for instance, turnover with organic products was 21.5 billion Euros in 2011 and showed a nine percent growth compared to the year before (FIBL 2013). The largest market for organic products was Germany and the highest market shares with five percent or more were reached in Denmark, Austria and Switzerland. Organic products are partly produced by organic agriculture and partly by the food industry using intermediate inputs from organic agriculture. Note that very few products from agriculture are directly sold to the end consumer.

Final demand for other green products is even harder to determine. To model the disaggregation into green and non-green sectors for the past and to maintain consistency, we therefore apply the reversed Leontief equation:

[3]

Final demand is thus calibrated in the historical model based on the input coefficient matrix corresponding to the estimated flow matrix and the estimated sectoral production.

Negative final demand denotes sectors where demand exceeds domestic production and the exceeding demand has to be covered by imports. Hence, the capability of the economy to replace imports with domestic production is limited. Generally, economies with low endowment of raw material resources like oil, gas or iron ore report negative final domestic demand in those sectors that use raw material for first production processes. In other industries, a negative final demand might be an indicator of, for instance, a high concentration of the production structure or low technological progress within the economy.

The model is calibrated on data for the historical development from 2005 to 2010. The most noticeable production took place in agriculture, waste, and water and, more recently, in renewable energy, electricity as well as solar water heaters.

3.3.The baseline scenario (0 – Basis)

The baseline scenario is a scenario which is only driven by GDP. GDP follows the exogenous growth path shown in Figure 10. No additional assumptions on green growth are made. Hence, all sectors grow with the same rate as GDP. Production is determined by using the Leontief production function. Employment, in turn, is driven by sector-specific production growth path. Direct and indirect employment is determined by applying the Leontief-multiplier. Also, the Tunisian solar plan is not included in the baseline scenario.

Total employment and production is given in Figure 14. The green and conventional part is shown in different colors. It illustrates that green employment has been in the past and remains also in the future – with all things being equal – a rather low portion of total employment. By 2030, total employment accounts to roughly 5 million persons of which 97% are employed in non-green industries. Total production reaches 386 billion TD in 2030. Most of it will be conventional production. Only 1.5% will be green-classified production.

Figure 14: Total employment & production (BASIS) – green and conventional

Source: own calculation.

The only sectors with visible green employment are agriculture, waste and water, and administration. In the business as usual world which characterizes the Baseline, also these sectors do not exhibit much additional dynamics.

Figure 15: Conventional and green production by sectors